A St. Louis man has admitted his part in a violent scheme to steal bitcoin from a Connecticut family. Martel Williams, 27, pleaded guilty Monday in federal court in Hartford to conspiracy to interfere with commerce by robbery, commonly called Hobbs Act robbery.
The charge carries a maximum sentence of 20 years in prison. U.S. Attorney David X. Sullivan announced the plea.
The plot began in August 2024. Prosecutors say the people coordinating the attack wanted bitcoin belonging to a man who had taken part in a theft worth hundreds of millions of dollars. To get it, they recruited Williams and two associates from St. Louis.
The crew was supposed to force its way into the target’s home, threaten him, and demand that he move the cryptocurrency into accounts the conspirators controlled.
Williams and others traveled to Connecticut between August 21 and August 24, 2024. They rented vehicles and gathered supplies, including air rifles, walkie-talkies, and a laptop computer. For two days, they stalked the target and his parents, waiting for an opening to get inside the house.
Cameras, frustration, and a failed bitcoin break-in
The opening never came. Williams and his associates feared they had been captured on home security cameras. They also grew frustrated with the plan and with a lack of communication from their coordinators. They left Connecticut without carrying out the job.
Shortly afterward, a second crew of six men from Florida arrived to carry out the scheme again. On August 25, 2024, Danbury police arrested those six men after a violent carjacking. The men beat and kidnapped two people inside the vehicle. Those two victims were the parents of the target.
Local outlets have tied the target to a bitcoin theft in the range of $230 million to $245 million, though the exact figure varies from report to report. The federal case itself centers on the attempted robbery, not the original theft.
Federal agents arrested Williams on July 17, 2026. He remains free pending sentencing, and no sentencing date has been set. The FBI New Haven Violent Crimes Task Force, FBI Los Angeles, FBI St. Louis, and the Danbury Police Department investigated the case. Assistant U.S. Attorneys Karen L. Peck and Stephanie T. Levick prosecuted it.
Other defendants in the Danbury case have also pleaded guilty, according to local reporting.
Poetic bitcoin justice
Earlier this month, a scammer who had stolen about 60 bitcoin (roughly $4.8 million) through a fake-review task scam lost it all when thieves emptied three Ledger addresses where the scammer had moved the proceeds on October 9.
Blockchain analysts at Chainalysis said the transfers went into one wallet reported as stolen, while the wider Ledger incident, in which a criminal group allegedly implanted seed-phrase-reading devices sold through Malaysian reseller CryptoBilis, may have drained about $86 million. Ledger said it was working with law enforcement and has confirmed no other vendors were targeted, following a July attack on Coldcard that cost users close to $120 million through a firmware bug.
At least 19 wallets linked to prediction market platform Predict.fun have reportedly been drained of approximately 105 ETH, worth $260,000, with investigators tracing the suspected stolen funds through Ethereum to cryptocurrency mixer Tornado Cash. On-chain investigator Naeven reported the suspected…
Highway thieves are using sophisticated digital tactics that investigators worry make it easy to rob trucks carrying millions in expensive data center equipment.
NBC News spoke to “several industry leaders, consultants, and investigators advising law enforcement” offices probing the biggest thefts yet and reported that since June, thieves have “made away with more than $100 million in data center freight.”
Here’s how they said thieves get away with it: First, thieves hack freight brokers’ accounts on shipment-listing websites and post fake shipments to lure real bids, then send a malicious link to any trucking companies that respond. Once victims click, thieves install software to take control of their accounts and start bidding on real shipments. Sometimes, a real delivery driver is hired to collect the cargo, unaware of the scam, and other times fake driver’s licenses are used to get accomplices hired. Either way, the goods are eventually transferred to a driver working with the thieves to resell the gear, and, in one of the largest thefts, tracking coordinates were spoofed to prevent digital monitoring.
Hardware wallet manufacturer Keystone has confirmed that hackers stole a device authentication key and exposed personal information belonging to 25,964 customers, forcing the company to destroy 18,835 devices and suspend shipments. According to the company’s October 26 security announcement, attackers…
October 2026 brought a clear demonstration that hardware wallets, while far safer than software alternatives, are not immune to sophisticated physical attacks.
Beginning on 9 October, hundreds of users who had purchased Ledger devices through the Southeast Asian reseller CryptoBilis saw their funds drained across Bitcoin, Ethereum, TRON and other chains. On-chain researchers estimated losses between roughly $86 million and more than $100 million. Ledger confirmed that at least one affected device contained an unauthorized hardware implant and stated that every confirmed loss in the incident was linked to a device sold by CryptoBilis. The company has emphasized that its own infrastructure, firmware and direct sales channels were not compromised.
The Supply-Chain Attack
The attack was physical. Someone in the distribution chain opened genuine Ledger Nano X devices, installed a small circuit board and resealed them. The implant sits inside the enclosure under or behind the screen where foam padding normally rests, and taps the SPI bus that carries data from the Secure Element to the display. When the owner sets up the device and the screen shows the 24-word recovery phrase, the implant’s microcontroller recognizes those screens, reconstructs the words and sends them out over LTE using a provisioned eSIM and a small antenna. Because the original Secure Element remains untouched, the device continues to pass Ledger’s Genuine Check. Mark Karpelès and Tibane Labs have documented multiple generations of the implant, progressing from early versions with visible wires and a smaller battery to later flex-circuit designs that are harder to notice and sometimes keep the original battery.
Source: Mark Karpelès
Mark Karpelès publicly posted a photo of a unit that arrived from Malaysia with flawless packaging. The extra hardware only became visible when he opened the case.
Source: Mark Karpelès
Similar implants have been reported in devices obtained through other channels, including Japanese marketplaces and at least one European store, although Ledger has so far tied every confirmed fund loss specifically to CryptoBilis purchases.
It was confirmed that the Ledger supply chain is compromised in Europe as well. Source: @0xJohannes_
The company has asked the reseller to halt sales and has advised recent buyers not to initialize unused devices. Those who already completed setup are told to move their assets to a new signer purchased directly from Ledger and initialized with a fresh seed phrase.
How to Buy a Hardware Wallet Safely
The single most effective protection is to purchase directly from the manufacturer’s own online store.
Authorized resellers are listed on the manufacturer’s website, yet CryptoBilis was also a partner that introduced modified units into the channel. Marketplace listings of third-party shops carry a much higher risk of both counterfeits and implants.
Once the package arrives, you should confirm that a new device requires you to generate a recovery phrase yourself on first use. Any recovery phrase that’s already written on a card or printed in documentation belongs to someone else and should never be used. The phrase must appear only on the device’s own screen and you must write it down yourself on paper or metal. Never type it into a computer or phone, don’t use websites or applications with it.
Below you can see a photo of the hardwallet owner signing a transaction inside the faraday cage to avoid any interference and possible theft.
Source: @oren_z0
Check Your Wallet
The first question is the source of the device. Anyone who bought a Ledger from CryptoBilis or another untrusted reseller in recent months should treat the unit as unsafe. Genuine Check is still worth running because it confirms that the Secure Element is original and the firmware is approved, yet it can’t detect added circuitry that merely listens to the screen.
You can also visually inspect the case for extra wires or antennas that can reveal tampering, but modern implants are designed to be inconspicuous and reliable detection usually requires opening the device. After a wallet is set up, compare receiving addresses shown on the device screen against those displayed in the companion application and review transaction history on block explorers for unexpected outgoing transfers. The recovery phrase must be generated by the device under your direct observation and written down only by you.
Mark Karpelès also has a few videos on opening and closing Ledger wallets that you might find helpful.
What to Do If You Suspect Compromise
If a device was purchased from CryptoBilis or any other questionable source and has already been initialized, the existing recovery phrase should be treated as compromised. Move your assets to a new wallet whose seed was generated on a trusted device bought directly from the manufacturer. Never reuse the old seed for any purpose.
More Recommendations
A BIP-39 passphrase adds a meaningful layer of protection because it isn’t displayed during ordinary setup and must be known in addition to the seed. It’s also known as passphrase (the extra “25th word”). It’s optional and you may choose it later. It is not generated or displayed by the device during ordinary setup. Adding it creates a hidden wallet, which means you have completely different keys and addresses.
For larger holdings use a multisignature arrangement to reduce reliance on any single device. Always check the address where you send your money to, as it can often be replaced by malware or bots making small transactions with similar addresses to mislead you into sending money to this similar address.
Hardware wallets still provide strong protection against the majority of remote thefts precisely because private keys never leave the Secure Element and every transaction requires physical confirmation on the device itself.
Summary
Hardware wallets can pass authenticity tests and still contain an implant capable of capturing the recovery phrase the moment it appears on screen. The best thing you can do is to buy devices only from the manufacturer, generate the seed yourself on the device and write it down offline. For anyone who recently purchased a device from a third party, the cost of generating a new seed and moving funds is far lower than the cost of discovering the compromise after the fact.
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Call it poetic justice: one of the biggest victims of last week’s Ledger theft happened to be a scammer themself, according to blockchain analysts, and lost nearly $5 million in bitcoin.
In a post Thursday, Chainalysis wrote that a crook lost 60 bitcoins worth about $4.8 million they’d stolen via a so-called task scam.
According to Chainalysis, the address was linked with a con where people were paid to fake sales and reviews of real items. They were told to add their own money in order to get paid — and then stolen from.
One of the biggest victims of the Ledger theft was a scammer themselves. They lost more than 60BTC, about $4.8M. The funds were from a task scam.
But the mastermind behind the task scam moved the stolen money to Ledger addresses which were then targeted by different scammers last week.
“On Sep 22, the person behind the scam moved the proceeds into three separate Ledger addresses,” Chainalysis said. “On Oct 9, thieves emptied all three. One transfer each, into the same wallet. The wallet is reported as stolen funds.”
Paris-based Ledger last week said it had started an investigation after customers in South East Asia reported they’d lost funds after buying from Malaysia-based reseller, CryptoBilis.
Ledger has since said that the scam was a massive organized crime operation where a group installed implants into devices and put them back on the market. The implants could read users’ seed phrases so criminals could then drain wallets.
Calling it one the most “sophisticated attacks” the digital asset industry has experienced, Ledger is yet to reveal how much money has been lost — but blockchain investigator Specter said $86 million had been drained.
And the task scam conman, according to Chainalysis, was one of the victims.
Ledger has said that it is working with law enforcement to “follow the funds and dismantle the attackers’ infrastructure” and has made sure no other vendors have been targeted by scammers.
CryptoBilis has stopped selling Ledger products, the company said.
Criminals have targeted bitcoin hardware sellers this year, with a huge attack taking place in July on the popular Coldcard products.
Crooks were able to steal close to $120 million in bitcoin from Coldcard users because the devices had a firmware bug which led to faulty seed generation, allowing hackers to guess investor seedphrases.
Social engineering is one of the most important parts of pentesting, and in many real attacks it’s the part that decides whether the whole operation succeeds or fails. Sometimes it even makes the technical side easier.
Earlier we looked at BadUSB attacks and several persistence methods, and those examples already showed how much can be done when a person simply plugs in a device or follows a convincing instruction. In a pentest, you can achieve real impact after just walking into an office and interacting with the environment without breaking into the corporate network remotely and hoping some serious vulnerability was left unpatched.
Many pentesters are stronger with systems than with people in everyday life. That’s one reason they gravitate toward technical work. Social engineering forces them to step out of that comfort zone even further. But understanding how people make decisions is a practical skill. When you design a scenario with human behavior in mind, the success rate of your interactions can rise. That’s why both red teams and blue teams will benefit from it.
Evolutionary Legacy
The brain is an old application. It’s software that has been running for thousands of years. New features have been added over time, but the core logic was never fully rewritten. Different developers came and went. Some old functions were never documented. Some code paths were never reviewed. The system kept growing, but the original structure remained inside it.
That is a pretty good description of the human brain.
Our brains are the result of evolution, and the most vulnerable mechanisms are often the oldest ones. These mechanisms helped our ancestors survive in situations where there was no time for deep analysis. We cannot delete that legacy. We can only learn to control it at a higher level of thinking. But the older layer is still there, and every person remains vulnerable to it in the right conditions.
Who Is More Vulnerable?
If you follow the media, you might get the impression that older people are always the easiest targets. Stories about elderly victims are emotionally powerful, so they get more attention. But that does not mean the data supports the stereotype in a simple way. Europol statistics on fraud victims who reported to the police show that the 18-34 age group made up 27.7 percent of victims, the 35-54 group 23.4 percent, the 55-64 group 21.7 percent, and the 65+ group 18.5 percent. That already shows that younger adults are very much in the picture. And that is only the official reporting side.
Age itself does not seem to make a person automatically more or less likely to be deceived. Cognitive ability also does not give the protection many people assume. A joint study by several American universities involving 1,220 participants found no meaningful correlation between cognitive ability and the likelihood of becoming a fraud victim. So being smart does not make you immune. Even very intelligent people can be tricked. Paul Frampton, a respected particle physicist and Nobel Prize candidate, was caught in a simple dating scam that led him to attempt to carry cocaine across a border. That case became famous not because he was foolish, but because it showed that intelligence alone does not protect a person from manipulation.
Vulnerable Optimization
The human brain has barely changed in size for thousands of years, but the amount of information we ask it to process has exploded. An ancient Greek farmer had roughly our brain and a tiny fraction of our information load. Today we face constant messages, deadlines, alerts, meetings, and decisions.
To cope, the brain optimizes. One of its oldest shortcuts is stereotypical sequential behavior (SPB). I’ve seen something like this before, so I’ll react quickly instead of thinking it through. This saves energy and speeds up decisions, which was vital for our ancestors since a fast response to danger could save a life. It’s the short route in thinking, faster and cheaper than analysis, and usually good enough.
Giving a logical reason can raise the success rate, but surprisingly, even a meaningless reason works almost as well. The brain didn’t evaluate the explanation, it simply reacted to the fact that one existed.
A phishing email with a short explanation (edited). Source: CaniPhish
Brain DoS
One of the easiest ways to force the brain into this energy-saving mode is to overwhelm it.
Emotional overload is one method. If someone triggers fear, stress, panic, or even strong excitement, they reduce the victim’s ability to think clearly. A frightened person doesn’t evaluate things carefully. They react, and that reaction is often automatic. Positive excitement can work too.
Hackers try to flood the brain with too much information from too many channels at once. A person trying to write a document, answer messages, listen to a coworker, and process notifications in the background will burn out mentally pretty fast. In that state, analysis gets difficult and the brain starts skipping into automatic behavior. That’s why overload is such a powerful social engineering tool. It pushes people away from deliberate thinking and into fast reaction.
A phishing email exploiting fear. Source: CaniPhish
Most Common Psychological Exploits
The psychology of influence contains many principles, and they show up everywhere, in marketing, advertising, sales, politics, therapy, and more. But for a hacker writing a phishing email or planning a phone script, only a few of these tend to matter most.
The three big ones are authority, scarcity, and consistency.
Principle of Authority
People naturally trust experts in areas where they themselves aren’t experts. If someone appears qualified, successful, wealthy, or powerful, we tend to listen. That’s part of how we navigate the world.
The real vulnerability is that authority can be faked.
People use white coats on television to sell toothpaste. So-called success coaches pose in front of expensive cars or Dubai skyscrapers to create an illusion of status. Well-known restaurant chains use actors from popular TV shows to advertise food. That’s exactly how fake authority works. The external costume creates the internal belief.
The Milgram experiment is a good demonstration of this. In 1963, participants were willing to obey an authority figure even when it made them uncomfortable and conflicted with their own moral instincts. The lesson is that authority has a very real psychological effect. Evolution plays a part here too. Human society developed through division of labor, and that made us more dependent on specialists. We got used to trusting experts. Hackers abuse that instinct all the time.
Here’s an example of a phishing email that appears to come from a manager and can’t be ignored.
A phishing email exploiting the principle of authority (edited). Source: CaniPhish
Principle of Scarcity
Scarcity is about the fear of missing out. People value things more when they are rare, limited, or disappearing. A product that says “only three left” feels more urgent. A limited-time offer feels more valuable. Even when the item is not actually better, scarcity makes it feel that way. This is an old human pattern. Imported or hard-to-find goods often seem more valuable than ordinary local alternatives, even when they are not objectively better. The absence of abundance created desirability.
Principle of Consistency
Consistency is one of the least obvious but most effective manipulation principles.
People prefer to be consistent with their earlier actions and statements. Society rewards consistency. A person who constantly changes their opinion is often viewed as unreliable or weak. A person who follows through is seen as stable and trustworthy. That social pressure matters a lot.
The problem is that being consistent is not the same as being correct. Once a person takes an initial step, they often become more willing to continue in the same direction. That saves mental energy and reduces self-doubt. It also fits the brain’s tendency to follow a behavioral script instead of starting analysis from scratch each time. Patricia Pliner’s study showed this clearly. Participants who first wore a badge supporting cancer research were later much more willing to donate to the cause. The first small commitment made the second one easier.
When a victim has already made a small commitment, continuing becomes easier than stopping.
Exploitation
To turn these principles into real social engineering operations hackers build scenarios. That scenario is most effective in a phone call, because a call allows hackers to guide the victim step by step and react to hesitation. Email phishing can also use these ideas, but the room for dynamic adaptation is smaller. The best phishing messages are not necessarily the loudest. They are the ones that fit the target’s mental state at the exact moment of delivery.
Emails and the 7% rule
In many social engineering assessments, a pattern appears again and again. When you send a large batch of phishing emails, a certain percentage of recipients will almost always act. The exact figure changes by organization, but the baseline rarely disappears.
Even when companies train users, run simulations and repeat awareness courses, there is often still a small percentage of people who click or respond. Why? Because at that moment, some of them are tired, stressed, busy, distracted or simply overloaded. At that moment, the person does not reach the analysis stage.
That is why training alone is not enough. Training helps, but it does not eliminate the human condition.
A phishing email triggering excitement. Source: CaniPhish
The most effective emails are often the ones that trigger stress or excitement directly. A message that creates urgency or a strong emotional reaction can overpower careful thinking. Once that happens, hackers move into the next steps.
Trigger Bypass Techniques
Most people have simple mental triggers that hold up even under pressure. The trick is that attackers can sometimes bypass those triggers by shifting the context.
A person might say they never share passwords. But that rule can get bypassed if the attacker presents a password generator, an IT support request, or a command they’re told to run for verification. The target can still believe they’re following their rule, even while being manipulated out of it. Verification habits can also be bypassed with fake signatures, familiar names, or a two-step sequence that starts with something safe. A short first interaction lowers suspicion, and then a second one carries the real pressure. That’s often more effective than starting aggressively. Company rules can be bypassed by changing the frame. A USB drive disguised as a personal gift feels different from an unknown device dropped on a desk. The same object reads very differently depending on the story around it.
That’s why social engineering isn’t about one universal trick. It’s about adapting the story to the trigger.
Protection
For companies, the best defense is a mix of organizational measures, technical controls, and incident response. Training lowers the success rate of simple attacks. Technical controls reduce the damage when someone does make a mistake. And since no defense is perfect, response procedures matter too. Organizations need to know what to do when a suspicious message, call, or request slips through.
Individuals should not be afraid to refuse. Don’t feel obligated to be polite when something feels wrong. If a call creates stress, stop and think instead of reacting automatically. Never make important decisions while overwhelmed. Learn to recognize manipulation patterns, and don’t keep a suspicious conversation going just because the other side sounds official.
Sometimes the safest choice is just to hang up.
Summary
There’s no guaranteed technique for success, and no guaranteed protection either. Human beings are vulnerable because evolution made us efficient, not perfect. That efficiency helps us survive, but it also gives social engineers a way in.
In April 2026, we at Kaspersky’s Global Emergency Response Team (GERT) responded to a security incident at a manufacturing organization in the Middle East. The threat actor obtained domain admin-equivalent control of the organization’s Active Directory environment and authored a malicious Group Policy Object (GPO) named PAYLOAD, linking it at the domain root. Through that single object, the actor delivered ransom notes, hijacked the desktop wallpaper and lock screen, enforced a logon banner, and disabled the local administrator account across every domain-joined Windows workstation — all without dropping a ransomware binary or encrypting any data. The only ransomware we found in this incident was PAYLOAD sample targeting ESXi on Linux servers. Besides that, data exfiltration was observed originating from the file servers and several additional systems, and was later published on the dark web.
Living-off-the-land abuse of trusted AD infrastructure. Group Policy is a signed, allowlisted, SYSTEM-privileged distribution channel that the majority of endpoint detection and response tools is designed not to inspect. By delivering impact through GPO rather than through malware, the actor sidestepped the entire file- and process-based detection stack.
Encryptionless extortion. Industry telemetry shows extortion-only incidents grow significantly year-on-year. PAYLOAD fits this model; the leverage is operational disruption and the threat of escalation rather than cryptographic denial of data.
We confirmed that no files were encrypted on Windows machines, no malicious binaries were resident on disk, no endpoint persistence was established, and no malicious processes were running at the time of analysis. The entire attack lived inside Active Directory itself. The defensive implication is stark: an organization whose detection strategy depends on catching a ransomware executable would have seen nothing until the first endpoint rebooted and the ransom wallpaper appeared.
In this article, we will describe the GPO attack chain and provide operational advice on how to detect such threats, including detailed remediation recommendations.
Group Policy as an attack surface
Attacks through group policies are nothing new. They can inflict significant, domain-wide damage with multiple malicious capabilities. A Group Policy Object (GPO) is essentially a combination of a Group Policy Container (GPC) in Active Directory and a Group Policy Template (GPT) in SYSVOL. The Group Policy scope depends on whether the GPC is linked to the directory tree at the domain, site, or organization unit (OU) level. A link at the domain root means the policy applies to every computer and user object beneath it. Thus, a GPO compromised at the domain root can affect all in-scope domain users and computers, potentially granting an attacker complete control over the corporate network. What makes GPO abuse even more dangerous is that group policies are processed in a trusted, high-privilege environment, ensuring persistence because endpoint cleanup is not enough to remove them.
We have already discussed GPO architecture and ways it can be compromised in greater detail in an earlier blog post. Other public threat intelligence has also repeatedly documented this technique in ransomware operations. Microsoft observed Ryuk operators distributing ransomware through Group Policy, SYSVOL startup items, and PsExec. LockBit affiliates have been documented modifying SYSVOL Group Policy files, including ScheduledTasks.xml, to support ransomware execution and propagation. BlackCat/ALPHV operators have also abused GPOs to create scheduled tasks and deploy ransomware.
Another notable example of GPO abuse is PAYLOAD ransomware, which weaponizes GPO Preferences and policy settings for pure impact rather than as a launcher for an encryptor. Let’s take a closer look at this attack, which is detailed further below.
Attack timeline
During the April 2026 investigation, we managed to reconstruct the attack timeline as outlined below:
Date
Event
11 April
Initial access. Threat actor authenticates to the FortiGate SSL VPN using a valid but compromised domain credential.
13 April
GPO authored. Malicious GPO, PAYLOAD ({C897F2C7-C2AC-4E6F-BF48-58036FF29E79}) created and linked at the domain root, configuring ransom notes, wallpaper, lock screen, logon banner, and administrator account disablement.
13 April
SYSVOL staging. The payload.jpg and hello.txt files written to \\DC.THECOMPANY.local\sysvol\THECOMPANY.local\.
13 April
Second GPO. GPO named win Firewall Off ({22099AD2-E062-4F56-B574-5099BBA4E7A6}) linked at the domain root, disabling Windows Firewall on all profiles.
13 April
Dormancy. GPO cached on endpoints but computer configuration not yet applied — no endpoint had rebooted since the policy update.
13 April
Data exfiltration. Data exfiltration was observed originating from the file servers and several additional systems.
14 April
Detonation. Most of the endpoints begin rebooting; computer configuration policies apply. Ransom wallpaper, logon banner, and notes appear. Operational disruption begins.
15 April
Response. Kaspersky GERT engaged. Forensic triage of affected workstations and the domain controller initiated.
16 April
Assessment. GERT confirms no file encryption, no resident malware, no endpoint persistence.
Next, we will discuss each of these stages in more detail and share the findings from our incident response activities.
Incident overview
Initial access
The entry vector was a compromised valid account (MITRE ATT&CK T1078) used to authenticate through the organization’s FortiGate SSL VPN — an external remote service (T1133). Insufficient logging on the FortiGate appliance prevented us from reconstructing how the credential was originally compromised.
Three hypotheses were considered plausible in the context of the attack, in no particular order:
Password spraying or credential stuffing against the SSL VPN portal.
Phishing-led credential harvesting.
Purchase of pre-compromised credentials from an initial access broker (IAB).
Once on the internal network, the actor operated with the compromised security principal’s privileges. Because the account was able to create and link a GPO at the domain root, it held either domain admin privileges or a delegated equivalent (e.g., membership of Group Policy Creator Owners combined with link rights on the domain object).
FortiGate SSL VPN authentication logs and ESXi/virtualization privilege escalation logs were insufficient to reconstruct the lateral movement and privilege escalation chain between initial VPN access and the GPO write privilege level. The most common real-world routes to GPO control — DCSync, Kerberoasting of privileged service accounts, and Pass-the-Hash/Pass-the-Ticket — could not be confirmed or ruled out.
Execution
Rather than deploying an encryptor, the actor abused the victim’s Active Directory policy infrastructure, resulting in malicious GPOs being configured and linked at the domain root to deliver the observed impact across domain-joined systems. The two GPOs below constitute the entire offensive toolkit observed.
The PAYLOAD GPO
We performed a Resultant Set of Policy (RSOP) analysis, which helped us list all policy settings on the affected workstations. From these results, we reconstructed the following changes delivered by PAYLOAD:
Drop SYSVOL\hello.txt to the desktop and root directories C:\ and D:\ as a read-only README-payload.txt by tampering with the “Group Policy Files” client-side extension (CSE).
Modify the HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System\ registry key, changing the legalnoticecaption value to "Welcome to Payload!" and the legalnoticetext to the ransom note text through the “Group Policy Registry” CSE.
Set payload.jpg located in the targeted domain controller’s SYSVOL as the lock screen image by altering the personalization policy, and as the wallpaper by altering the desktop policy at the user level.
Revoke administrator rights for the administrator account (locking the account) by editing the Security Settings CSE in the GptTmpl.inf file.
Settings changed by PAYLOAD GPO
This activity was enabled entirely through a legitimate group policy mechanism, meaning there is no malware code for security solutions to look for because the malicious logic is contained within the policy configuration.
The win Firewall Off GPO
A second domain-root-linked GPO, named “win Firewall Off”, disabled Windows Firewall across the domain, private and public profiles on all endpoints (T1562.004). Deployed independently of PAYLOAD, this object degraded host defenses and ensured the actor retained unimpeded network reach to endpoints for any follow-on activity.
Settings changed by win Firewall Off GPO
The one-day delay detonation
The most forensically instructive detail is the one-day gap between GPO creation (13 April) and visible impact (14 April). Analysis of Master File Table (MFT) timestamps and the Group Policy History registry key confirmed the policy was written to SYSVOL and cached on endpoints on 13 April. However, computer configuration settings (wallpaper and lock screen machine policy, security settings, firewall disabling) only apply upon reboot or policy refresh — and no endpoint had rebooted in the interim. The attack therefore remained dormant in the GPO cache for one day before detonating en masse when machines were restarted in accordance with standard procedures.
We have to point out here that this delayed policy application is characteristic of GPO-based operations and has two potential consequences for defenders. Firstly, it may grant the actor a quiet window for exfiltration, persistence, or further staging between weaponization and impact. Secondly, it can be used to sever the temporal link between the cause (a GPO-creation event in the directory log) and the effect (mass user-visible disruption occurring at a later time), complicating timeline reconstruction unless directory service auditing is in place.
Forensic findings
Initial incident response engagement revealed a number of findings associated with the attack that we share below.
No file encryption
A full review of the MFT on affected workstations found no files bearing a .payload extension characteristic to PAYLOAD ransomware and no evidence of bulk renaming or encryption I/O patterns. The attackers’ objectives were operational disruption and extortion via visual impact and access denial.
No endpoint persistence
All standard persistence locations were clean:
Scheduled tasks — no malicious tasks
Run/RunOnce keys — clean
Startup folders (user and system) — clean
Services — no malicious service installed
WMI event subscriptions — none
Boot sector/MBR — unmodified
The attack’s persistence mechanism is the GPO link itself on the domain controller, with no endpoint-resident component.
No active malicious processes
Live process and memory analysis revealed no injected threads, process hollowing or anomalous outbound connections.
Registry timeline analysis
Group Policy History, Shadow and State registry keys on the workstation recorded the application of PAYLOAD on 13 April:
HKLM\…\Group Policy\History\{35378EAC-683F-11D2-A89A-00C04FBBCFA2}\1
HKLM\…\Group Policy\Shadow\{827D319E-6EAC-11D2-A4EA-00C04F79F83A}\0
HKLM\…\Group Policy\State\Machine\GPO-List\7
HKCU\…\Group Policy\History\{7150F9BF-48AD-4da4-A49C-29EF4A8369BA}\1
HKCU\…\Group Policy\State\S-1-5-21-…\Loopback-GPO-List\5
The presence of the “Loopback-GPO-List” entry indicates the GPO was processed in loopback mode, ensuring the user configuration (wallpaper) applied regardless of which user logged on to the machine.
SYSVOL artifacts
Two files were staged on the domain controller’s SYSVOL share and served to endpoints through the Files Group Policy Preference CSE:
payload.jpg — the ransom image used for both wallpaper and lock screen.
hello.txt — the ransom note, distributed to desktops and drive roots as README-payload.txt.
Detection engineering
Because no malicious binary or process exists, the detection logic should focus on the directory service and SYSVOL indicators. Below are the highest-value telemetry sources for identifying the described malicious activity.
Directory service change auditing (DS Access)
Enable Advanced Audit Policy → DS Access → Audit Directory Service Changes on all domain controllers and set up alerts for the following events:
Event ID
Meaning
Hunt focus
5137
A directory service object was created
The account that created new groupPolicyContainer objects must be an authorized GPO administrator
5136
A directory service object was modified
Changes to gPLink on the domain root or sensitive organizational units; changes to gPCMachineExtensionNames/gPCUserExtensionNames/gPCFileSysPath/versionNumber for all GPOs
5141
A directory service object was deleted
GPO deletions (relevant for tamper detection and remediation assessment)
A gPLink modification at the domain root by a non-standard account is one of the most telling indicators of this attack class.
SYSVOL file integrity monitoring
Monitor \\DC.THECOMPANY.local\sysvol\THECOMPANY.local\Policies\ for unexpected files, particularly image files, text files, scripts, ScheduledTasks.xml, and modified registry.pol/GptTmpl.inf files that were created by sources other than legitimate replication.
Endpoint policy application telemetry
On endpoints, GPO application is logged in the Group Policy Operational log (Microsoft-Windows-GroupPolicy/Operational) and reflected in the History and Shadow registry keys shown above. A sudden domain-wide change to the applied policy set is a strong post-detonation signal.
Missing 5136 events
If the contents of a GPO’s SYSVOL change without a corresponding 5136 event, this can indicate direct SYSVOL/template editing (e.g., via open-source tools such as PowerView or SharpGPOAbuse) that bypasses the normal Group Policy Management Console (GPMC) modification path. While we recommend treating the absence of expected audit events as suspicious, it should be noted that this can be caused by misconfigured auditing.
Anti-forensics and recovery-inhibition capabilities
Confirmed PAYLOAD family capabilities
The Windows endpoint attack described in this report was implemented through malicious Group Policy Objects and did not involve a recovered ransomware executable, resident endpoint malware, confirmed file encryption or active malicious processes at the time of the forensic examination. However, PAYLOAD cryptomalware for Windows does exist, and other sources, including public analysis of its samples, reveal further malicious capabilities of this ransomware that could be used by security teams to enrich detection logic and security policies.
The behaviors documented in this section must therefore be interpreted as family-level capabilities identified through the public reverse engineering of PAYLOAD ransomware samples. They were not confirmed as having executed during the GPO-based incident unless corresponding evidence was identified in the host, memory, process, event-log, or hypervisor.
Windows Event Log clearing
Public reverse engineering of the PAYLOAD Windows variant reveals an optional event log clearing capability (T1685.005, formerly T1070.001). The ransomware dynamically resolves Windows Event Log APIs, enumerates available event log channels, and clears individual channels.
Implementation artifacts include:
Runtime loading of wevtapi.dll
EvtOpenChannelEnum
EvtNextChannelPath
EvtClearLog
Enumeration of Security, System, Application, and PowerShell logs, and operational channels
A command-line option controlling whether log clearing is performed
Clearing event logs reduces the availability of records related to process execution, authentication, PowerShell, service control, and system changes. However, it does not necessarily remove events that were already forwarded to a SIEM, Windows Event Collector, EDR backend, or protected log archive.
Forensic indicators
Windows Security Event ID 1102
Event logging shutdown or failure events
Sudden reductions in event record identifiers
Multiple event channels restarting from low record numbers
Gaps between endpoint and centrally forwarded telemetry
Execution of utilities or APIs associated with log management
Direct access to EVTX files (Windows Event Log files) under the Windows event log directory
We should note that these indicators can’t be interpreted on their own. For instance, Event ID 1102 should be correlated with a number of aggravating factors, such as:
Event ID 4688 or Sysmon Event ID 1 for process creation
Event ID 4624 for the associated administrative logon
EDR process trees
PowerShell operational logging
Windows Event Forwarding records
Privileged access management activity
At the same time, the absence of Event ID 1102 does not prove that log clearing did not occur. Direct deletion, truncation, service impairment, or an incomplete audit configuration may produce different evidence.
Security process and service termination
PAYLOAD analysis reveals that the Windows ransomware variant contains logic that targets security processes and services (T1685 and T1489). This capability is intended to stop security products, backup software, database services, and applications that may lock files targeted for encryption.
Process and service termination serves several objectives:
Reduce endpoint detection and response visibility.
Release file handles so data can be modified.
Interrupt backup and recovery services.
Prevent databases and enterprise applications from protecting active data.
Reduce interference with encryption operations.
Forensic indicators
Security agent services changing from running to stopped
Event ID 7036 service state changes
Event ID 7040 service start type changes
Event ID 4688 or Sysmon Event ID 1 for service control utilities
Sysmon Event ID 5 for terminated processes
EDR health degradation affecting many endpoints
Repeated termination attempts against security or backup processes
Execution of dedicated process killing utilities
VSS deletion, backup and recovery suppression
Public PAYLOAD sample analysis reports the deletion of Windows Volume Shadow Copies before encryption (T1490). This behavior removes local restore points and reduces the victim’s ability to recover files without external backups.
Recovery inhibition is broader than VSS deletion and may include multiple other malicious techniques, including the following:
Deleting shadow copies, backup catalogs, and hypervisor snapshots
Disabling recovery services
Modifying boot recovery settings
Compromising backup management platforms
Deleting or encrypting backup repositories
In the PAYLOAD Windows sample that is proven to perform encryption, VSS deletion is confirmed to have taken place before encryption. A broader compromise of the backup platform was not established in the investigated incident.
Forensic indicators
Execution of shadow copy management utilities
Backup catalog deletion attempts
Recovery configuration changes
Backup service termination
Mass snapshot deletions
Backup administrator logons outside normal maintenance windows
Backup retention or immutability changes
Backup jobs failing immediately before disruptive activity
Ecosystem-relevant ransomware techniques
Above, we discussed the techniques specific to PAYLOAD ransomware. In this section, we’ll review other common ransomware techniques, such as BYOVD abuse and ESXi policy weakening, that remain relevant risks in the ransomware ecosystem. However, these techniques should not be attributed to this incident without supporting driver load, process, memory, ESXi, vCenter, or backup platform telemetry. We describe these techniques below as they may prove useful in other ransomware-related forensic investigations.
The examples used in this section are therefore ecosystem-relevant: they are commonly observed in ransomware operations but not conclusively attributed to the analyzed PAYLOAD samples.
ETW suppression and in-memory patching
Event Tracing for Windows (ETW) is a kernel-supported tracing architecture used by Windows components, diagnostic utilities, security products, and endpoint monitoring systems.
Although we didn’t encounter this technique in our case, some ransomware families can patch ETW-related functions inside the ransomware process (T1685, formerly T1562.001). The reported routine changes the memory protection of code pages, overwrites the beginning of selected ETW functions so they return without producing events, restores the original protection, and refreshes the instruction cache.
Reported target functions include EtwEventWrite, EtwEventWriteFull, EtwEventWriteTransfer, and EtwRegister.
This modification applies to the process-local mapping of ntdll.dll. It does not disable ETW globally across Windows, but it can reduce the telemetry generated by the modified process.
Forensic indicators
Writable or recently modified executable pages within ntdll.dll
Memory protection changes affecting ETW function addresses
In-memory code differing from the corresponding clean DLL on disk
EDR memory tampering alerts
Unexpected calls to memory protection APIs followed by telemetry silence
Process execution visible in network or filesystem telemetry but absent from expected ETW-derived sources
Inconsistent telemetry between EDR, Sysmon, Windows Event Logs, and network monitoring
It should be noted that telemetry gaps are not conclusive evidence of ETW patching. Other factors include agent upgrades, network outages, endpoint shutdowns, SIEM ingestion failures, collector backpressure, and filtering or licensing changes.
Memory acquisition is the strongest validation source when process-local ETW patching is suspected.
Vulnerable signed driver abuse, BYOVD
Bring Your Own Vulnerable Driver (BYOVD) involves introducing or abusing a legitimately signed but vulnerable kernel driver (T1068 and T1685). The attacker exploits the driver’s exposed functionality to gain kernel-level capabilities, modify protected memory, terminate security processes, remove security callbacks, or bypass operating system security controls.
BYOVD is highly relevant to contemporary ransomware operations. However, the reviewed public PAYLOAD analyses do not provide sufficient evidence to conclude that BYOVD is an intrinsic PAYLOAD capability.
It should therefore be presented as an ecosystem-relevant technique rather than a confirmed PAYLOAD feature.
Forensic indicators
Unexpected .sys files written to user-writable or temporary directories
New kernel driver services
Sysmon Event ID 6
Driver hashes matching Microsoft or community vulnerable driver blocklists
Invalid, revoked, expired, or unusual driver signatures
Driver load followed by EDR termination
New privileged processes immediately following driver loading
Code Integrity or Defender alerts
Service creation events referencing driver files
ESXi security policy weakening
Ransomware operators are increasingly targeting ESXi and vCenter because compromising the virtualization layer provides access to many business-critical virtual machines.
Public research typically describes operators performing the following activities (T1685, T1490 and T1489):
Enabling SSH on ESXi hosts
Changing root passwords
Disabling execInstalledOnly
Modifying lockdown mode exceptions
Stopping virtual machines
Deleting snapshots and backups
Changing host firewall policies
Copying custom ransomware binaries to hypervisors
On the target organization’s Linux servers we saw an ESXi PAYLOAD variant, which makes this behavior operationally relevant. Nevertheless, the reviewed evidence does not indicate that PAYLOAD operators used any of these policy-weakening actions in the investigated incident.
Forensic indicators
Unexpected ESXi SSH enablement
Changes to execInstalledOnly
Secure Boot enforcement changes
Lockdown mode configuration changes
Root password changes
New or unusual administrator accounts
Bulk VM shutdown activity
Bulk snapshot deletion
New binaries in datastore or temporary paths
vCenter tasks originating from unexpected accounts or systems
Missing or disabled remote syslog forwarding
Remediation
To contain the described threat and limit possible damage, several remediation steps should be taken. Below, we recommend a four-phase remediation approach for containing this threat and restoring the affected environment.
Phase 1 — domain controller actions (to be performed first)
When dealing with PAYLOAD GPO, the first priority of the remediation plan should be to remove the source GPOs. Until this is done, endpoint cleanup is ineffective because the next policy refresh re-infects cleaned machines.
The immediate domain controller actions to be taken are:
Delete PAYLOAD GPO. Remove {C897F2C7-C2AC-4E6F-BF48-58036FF29E79} via GPMC.
Delete or revert win Firewall Off GPO. Remove {22099AD2-E062-4F56-B574-5099BBA4E7A6}.
Clean SYSVOL. Delete jpg and hello.txt from \\DC.THECOMPANY.local\sysvol\THECOMPANY.local\.
Rotate credentials. Reset the compromised account; audit all privileged accounts and group memberships for unauthorized changes; rotate krbtgt twice if domain admin compromise is confirmed.
Force refresh. Perform gpupdate /force across endpoints after deletion; re-enable local administrator and firewall via clean policy.
Phase 2 — Active Directory and GPO hardening
Adopt the AD tiered administration model and confine domain admins to Tier 0 with no interactive logon to workstations and member servers.
Separate GPO creation from GPO linking rights, and grant both only to a dedicated, audited administrator role.
Enable GPO change auditing (Event IDs 5136, 5137, 5141) and forward to a SIEM.
Monitor SYSVOL with file integrity tooling.
Phase 3 — credential and access hardening
Enforce phishing-resistant MFA on all VPN and remote access entry points.
Deploy Windows LAPS to generate unique, rotated local administrator passwords.
PAYLOAD demonstrates a maturing tactic of turning the victim’s own trusted infrastructure into a weapon. By weaponizing Group Policy, the actor achieved a domain-wide impact without a single malicious binary on any endpoint, evaded file- and process-based detection entirely, and caused organization-wide disruption within seconds of the first reboot.
The absence of encryption is the most strategically significant finding and is consistent with the 2026 trend toward encryptionless extortion. At Kaspersky GERT, we assess with moderate confidence that the missing encryption reflects one of two scenarios: (1) a deliberate decision to stay below the irreversible data destruction threshold while preserving the option of a follow-on encryption phase, or (2) an operation interrupted before full execution.
The absence of encrypted files must not be mistaken for the absence of a serious compromise — the most critical impact lies in the actor gaining domain admin-level control. This incident proves that a threat actor with domain admin access and a working knowledge of group policy internals can inflict domain-wide disruption equivalent to a ransomware attack without writing a single malicious file to any endpoint.
Detection strategies anchored solely in file- or process-based indicators are blind to this attack class. Effective controls include directory service change auditing, SYSVOL integrity monitoring, and privileged access governance, which allow for GPO protection.
Detection by Kaspersky solutions
Kaspersky security solutions effectively detect the described malicious activity at various stages of the attack. Possible detection scenarios are listed below.
To protect organizations that use our Kaspersky SIEM system, we have prepared a package of correlation rules designed to help detect this type of malicious activity. The rules are now available for customers to download from the SIEM repository; the package name is: [OOTB] Group policy hijacked: PAYLOAD ransomware – ENG.
The “Group policy hijacked: PAYLOAD ransomware” package contains rules that detect suspicious file creation or modification in the SYSVOL shared folder on a domain controller, as well as changes to critical attributes and settings of domain group policies. Some rules may require adjustment if they trigger in response to legitimate activity, such as synchronization between domain controllers or the configuration of a new group policy.
To ensure the detection rules function correctly, verify that events from Windows systems are being received in full, including events with the following identifiers: Sysmon: 11, Security — 4663, 5136, 4657.
We also recommend applying the following rules available in the repository to detect all attack stages.
Detection of Windows Event Log clearing to cover up traces of an attack: R050_03_Windows Event Log was cleared
Detection of suspicious access to the LSASS process, which may indicate attempts to dump credentials: R262_Suspicious access to the LSASS process
Detection of the Volume Shadow Copy service being started, which is used to create shadow copies before deleting them: R231_20_Running the Volume Shadow Copy service
Detection of shadow copy deletion: R321_Shadow copy deletion
Detection of Windows Defender disablement: R076_01_Windows Defender Antivirus was disabled
Detection of attempts to disable or modify the system firewall: R240_03_Disabling system firewall via the registry
Detection of a service installation from a non-system folder, which may indicate malware persistence techniques: R281_01_Installation of a service from a non-system folder
For the rules in this list to function correctly, it is necessary to configure Security event auditing for event IDs 4663, 5136, 4657, 7036, and 1102.
In addition to the SIEM system, when audit settings are configured correctly, the process of creating, modifying, and deleting GPOs generates a large number of characteristic artifacts on the domain controller, enabling Kaspersky Endpoint Detection and Response Expert to promptly alert the user to anomalies in the infrastructure.
The creation of a new GPO is covered by the gpo_creation rule, which triggers in response to the corresponding event in the infrastructure. Changes to existing policies are detected by the following rules:
The setting_the_gpcfilesyspath_attribute rule detects the use of the gPCFileSysPath attribute of a Group Policy Object, which specifies the path to the GPO’s contents in SYSVOL.
In the next major version update of Kaspersky EDR Expert, a new event type, GPO, will be introduced, allowing users to track changes to Group Policy Objects.
For information security officers, GPO events will serve as an additional source of context when investigating activity in Active Directory and will help detect changes that could affect the configuration, access rights, and security of endpoints before a potentially malicious policy is deployed.
MITRE ATT&CK mapping
Tactic
Technique
Observed behavior
Initial Access
T1078 — Valid Accounts
Compromised domain credential used for VPN authentication
Initial Access
T1133 — External Remote Services
FortiGate SSL VPN used as entry point
Privilege Escalation
T1078.002 — Domain Accounts
Account held domain-level GPO create/link rights
Privilege Escalation/Defense Impairment
T1484.001 — Group Policy Modification
Malicious PAYLOAD GPO created and linked at domain root; re-applies on every refresh/reboot; uses trusted channel to evade EDR
Defense Impairment
T1686 — Disable or Modify System Firewall
win Firewall Off GPO disables Windows Firewall on all profiles
Impact
T1491.001 — Internal Defacement
Wallpaper and lock screen replaced with ransom image
Impact
T1531 — Account Access Removal
Local Administrator account disabled via GPO Security Settings
Collection
T1005 — Data from Local System
Data exfiltration was observed originating from the file servers
Command and Control
T1071 — Application Layer Protocol
No live C2 confirmed; delivery achieved entirely via GPO
Indicators of compromise
GPOs
PAYLOAD ransomware GPO: {C897F2C7-C2AC-4E6F-BF48-58036FF29E79}
win Firewall Off GPO: {22099AD2-E062-4F56-B574-5099BBA4E7A6}
File names and MD5 hashes
payload.jpg: Ransom wallpaper and lock screen image (SYSVOL)
hello.txt: Ransom note source (SYSVOL)
README-payload.txt: Ransom note dropped to desktops and drive roots
killer.exe (0108656A3E1ADE6CA4F21B084F5E1208): process killer tool
kill.exe (BEA5E267F24D7DA59F6821BFFDBFF293): process killer tool
We have been tracking two new backdoors, OctLurk and SilkLurk, observed in attacks against government organizations primarily in Central Asia since January 2025. Identified victims are located in Afghanistan, Kyrgyzstan, Tajikistan, Uzbekistan, Kazakhstan, and the Syrian Arab Republic. These organizations operate across several sectors, including healthcare, research, government offices, ministries of foreign affairs, logistics, law‑enforcement agencies, urban planning and facilities management, and public educational establishments.
The backdoor loaders are customized for each victim and use information from the victim’s machine to decrypt the payload. Both the loaders and the backdoors are heavily obfuscated, making analysis more complicated. OctLurk and SilkLurk can download and inject additional plugins to perform further malicious actions, including launching command shells, performing file system activity, synthesizing keyboard and mouse events, network scanning, credential dumping, keylogging, password theft from browsers, email collection, and remote access. Furthermore, the attackers deployed a specialized utility we named LurkProxy, which we also cover in this report. While it has a highly similar architecture to the OctLurk backdoor, it is not a backdoor itself.
Our investigation shows that the same threat actor operates both SilkLurk and OctLurk , and some victims infected with SilkLurk also contain OctLurk. We assess with medium confidence that the same actor is behind both backdoors, and that they are Chinese‑speaking. However, at the time of publication, we couldn’t attribute this activity to any known group.
OctLurk
OctLurk Deployment
The attacker created a scheduled task named GoogleUpDate on remote machines using admin credentials. The task runs once with System account privileges right after it was created, executing the batch script located at C:\Users\<username>\Videos\1.bat (MD5 6ecf84fb18f6747ed08d7598364d853a). Prior to executing the task, the actor queries its status. It is then run, as shown below.
The 1.bat script creates a service named NgcCIntSvc, which loads the loader DLL named oleasapi.dll (MD5 082d49ef9f14e6811d68c7e0e82e5069). The ServiceMain parameter in the service’s registry entry is set to invoke the RegisterService function of oleasapi.dll as shown below.
LurkPoxy Deployment
In another case, the attacker at first checked connectivity to the domain dns[.]ssentialserv[.]xyz as shown below. At the time of our research, the domain was resolving to the address 154[.]196[.]162[.]76 which is used as a LurkProxy C2 server.
After confirming that the C2 server was reachable, the attacker executed the batch script C:\Users\[username]\Desktop\auto.bat (MD5 b874123a80fc4f40e06872b9cb54ebc6). The script created a service named Cusrxsrv, which loads a DLL named msbasesysdc.dll. In the service registry, the ServiceMain parameter was set to call the RegisterService function of msbasesysdc.dll as shown below.
We identified several service names — specitsrc, cmtastsvc, PNRPHostSvc, vmictimerosync, and vmicagent — that the attackers used to load a malicious DLL onto compromised machines.
OctLurk loader
The loader DLL exports two methods, Refresh and RegisterService. The previously created service first calls RegisterService, which in turn invokes Refresh, the method that contains the malicious code. To locate the payload, the loader double-XOR-decrypts and then zlib-decompresses a set of hard‑coded bytes, yielding the payload file path. The payload bytes itself undergoes the same double‑XOR decryption and zlib decompression to produce the backdoor DLL bytes.
The double‑XOR decryption uses two distinct multibyte keys:
Key 1: hard‑coded in the loader
Key 2: derived from the serial number of the C: drive
The backdoor DLL is reflectively injected into memory and its entry point is executed. The loader can then call the DLL’s exported methods either by name or by ordinal; both the method name and the ordinal number are hard‑coded in the loader and are decrypted using the same double‑XOR and zlib‑decompression process applied to the payload path and bytes.
OctLurk backdoor
The loader invokes the backdoor’s curl_easy_escape function (ordinal 2). The backdoor then creates a stream socket using a hard‑coded C2 address (dns[.]multitoconference[.]com) and port 443. It gathers the following information from the victim machine:
OS information as RTL_OSVERSIONINFOW structure
Computer name
User name
Local host name
Local IP address in format %u.%u.%u.%u, with local hostname-to-IP-address translation
Current local date and time as SYSTEMTIME struct
To encrypt the collected data, the backdoor employs a hard‑coded XOR key, which in most cases we observed was the string FDrertgr##@QEWASGkio865ehyf98foidsjzhug874392dfsREFDfdsAGH43wea98h. In addition, it generates 0x53 (83) random bytes — this length is also hard‑coded in the sample — and uses them as a second XOR key. The collected victim information is first compressed with zlib (deflate), and then XOR‑encrypted twice, first with the hard‑coded string key and then with the randomly generated byte sequence. The final data is arranged as follows:
The backdoor initially transmits a 16‑byte header that specifies the size of the incoming data packet, as shown below. It then sends the actual data packet.
0x00: randomly picked 10 chars from the string “zyxwvutsrqponmlkjihgfedcbaABCDEFGHIJKLMNOPQRSTUVWXYZ9876543210-_”
0x0A: \x00\x00
0x0C: next_packet_size
The first packet received is 16 bytes long, and its last four bytes specify the size of the subsequent data packet. The format of the subsequent data packet is shown below.
0x00: XOR key; size 83 bytes
0x53: compressed data size
0x57: compressed data in the format: <uncompressed_size> <deflate(data)>
The received data is decrypted using a double‑XOR method: first with the XOR key contained in the packet, then with a hard‑coded XOR key. After the XOR decryption, the data is zlib decompressed. The data may be a command or a plugin code.
OctLurk loads plugins from the C2 server directly into memory to perform various tasks. Each plugin exports two methods — ins_ctl_db and oct_lk_col — with the actual functionality implemented in oct_lk_col. Our analysis shows that the plugins listed below are commonly deployed on victim machines.
Command Shell: provides a command shell
File Manager: performs filesystem interaction
Interaction Manager: synthesizes keyboard and mouse events
The table below provides a detailed description of operations performed by these plugins, where each switch case value denotes command ID.
Plugin type
Description
File Manager
● case 0x10020: for each drive, retrieve the following information: volume GUID path, drive letter, volume name, file system name, drive type, volume serial number, total size in bytes, and free space in bytes.
● case 0x10030: search for a file that matches a specified name and retrieve the following information: file attributes, creation time, last access time, last write time, file size, the file’s name, and its short (8.3) name.
● case 0x10040: recursively list all files in a specified location, including only those whose size, creation time, last write time, and last access time fall within the threshold values defined by C2. For each listed file, retrieve the following details: file attributes, creation time, last access time, last write time, file size, file name and alternative name for the file
● case 0x10050: use the ShellExecuteExW API to open the specified file path, which may be an executable, a document, or a folder.
● case 0x10051: execute the specified command line using the CreateProcessAsUserW API.
● case 0x10060: perform the following file‑system operations: copy, delete, move, and rename — using the SHFileOperationW API.
● case 0x10070: create a directory.
● case 0x10080: set the attributes for a file or directory.
● case 0x10090: for the filename provided by C2, set the file created, last accessed, and last modified timestamps to the values received from C2.
● case 0x20010: get the size of a file.
● case 0x20020: read a file from the system in chunks, starting at a specified offset.
● case 0x20030: calculate the CRC32 of each file data chunk, and retrieve the file created, last accessed, and last written times.
● case 0x20040: close the file handle and free the associated metadata (file path, handle, and size).
● case 0x20110: create a file at the specified path and write the bytes received from C2 into it. Then set the file created, last accessed, and last modified times using the timestamps supplied by C2.
Command Shell
● case 0x3E9: launch cmd.exe as shell.
● case 0x3EA: send the exit command to close the command shell.
● case Default: if a command string is received from the C2 and the shell is running, write the command to the shell. Then read the shell’s output and send it back to the C2.
If a command string is received from the C2 server and the shell is not already running, execute the command using C:\Windows\System32\cmd.exe /S /C "<command_string>" > %TEMP%\tmp%d%x.tmp where %d and %x are random values. Afterwards, read the output from the temporary file tmp%d%x.tmp and then delete the file.
Interaction Manager
● case 0x3E9: capture the entire screen as a BMP image.
● case 0x3EA: capture the entire screen at specified intervals.
● case 0x3EC: retrieve clipboard data.
● case 0x3ED: copy the data to the clipboard.
● case 0x3F3: MOUSEEVENTF_LEFTDOWN: set the cursor to the specified position and press the left mouse button.
● case 0x3F5: MOUSEEVENTF_LEFTDOWN | MOUSEEVENTF_LEFTUP: move the cursor to the specified position, then press and release the left mouse button.
● case 0x3F6: MOUSEEVENTF_RIGHTDOWN: set the cursor to the specified position and press the right mouse button.
● case 0x3F7: MOUSEEVENTF_RIGHTUP: set the specified cursor position and release the right mouse button.
● case 0x3F8: MOUSEEVENTF_MOVE: move the mouse cursor to specific coordinates, simulating a mouse movement event.
● case 0x3F9: MOUSEEVENTF_WHEEL: move the mouse wheel by a specified amount.
● case 0x3FD: press the key indicated by the virtual‑key code.
● case 0x3FE: KEYEVENTF_KEYUP: release the key identified by the virtual-key code.
● case DEFAULT: MOUSEEVENTF_LEFTUP: move the cursor to the specified position and release the left mouse button.
Post-compromise activity
The attacker used the command‑shell plugin installed via the OctLurk backdoor to perform the following actions:
Victim fingerprinting
The attacker used admin credentials to create a scheduled task named GoogleUpDate on remote machines. This task runs once with System account privileges, executing the script located at C:\windows\temp\in.bat (MD5 45cf5916fab4272a1313c26e67aa9220, 4e6d5c4770d5a822d7fcce6a74f7ad73). After querying the task’s status, the attacker triggers its execution, as shown below.
The batch script runs a series of commands that collect comprehensive information about the machine’s hardware, software, and network configuration as shown in the table below. The results are saved in three files — info.txt, <hostname>.datb, and <hostname>_logs.datb — all stored in the %TEMP% directory.
Command
Description
chcp 1256
Changes the system’s code page to 1256, which supports Arabic characters.
powershell $PSVersionTable
Retrieves the version information of PowerShell.
qwinsta
Views all active sessions on the local machine.
klist sessions
Displays a list of logon sessions on this computer (Including Kerberos).
TASKLIST /V
Lists all running tasks with detailed information.
findstr /i /c:”explorer.exe”
Searches for explorer.exe in a case-insensitive manner. Used together with TASKLIST /V.
wevtutil qe Security /f:text /c:5 /rd:true /q:”*[System[(EventID=4624)]] and *[EventData[Data[@Name=’LogonType’]=10]]”
Retrieves the last 5 events from the Security event log where the event ID is 4624 (successful logon event) and the logon type is 10 (remote interactive logon e.g., Remote Desktop Protocol).
Displays detailed information about the current user, including their security identifiers (SIDs), privileges, group memberships, and authentication details.
Searches the Windows Registry under HKEY_LOCAL_MACHINE (HKLM) for entries where the value name is “ProfileImagePath” and the type is REG_EXPAND_SZ. It points to the location of a user’s profile folder.
cmd.exe /c dir /b c:\users
Lists the contents of the C:\Users directory.
wmic startup get caption,command | findstr exe
Filters startup items for executable files.
powershell “get-MpComputerStatus”
Retrieves the status and configuration details of Microsoft Defender Antivirus (formerly Windows Defender) on a Windows system.
Queries exclusion settings for Microsoft Defender Antivirus. This is where you can configure files, folders, processes, and extensions that should be excluded from being scanned by Defender.
wevtutil gli Security
Configures the Security event log.
wevtutil gl Security /f:xml
Retrieves events from the Security log in XML format.
wevtutil gli “Windows PowerShell”
Configures the Windows PowerShell event log.
wevtutil gl “Windows PowerShell” /f:xml
Retrieves events from the Windows PowerShell log in XML format.
wevtutil gli System
Configures the System event log.
wevtutil gl System /f:xml
Retrieves events from the System log in XML format.
schtasks /query /fo LIST /v | findstr “TaskName> Status> ‘Task To Run’> ‘Run As User’>”
Lists all scheduled tasks in verbose mode and extracts the following fields: Status, Task To Run, Run As User, and TaskName.
Provides network configuration details, such as IP address, DNS, DHCP status, etc.
ipconfig /all
Displays detailed network configuration.
netstat -e -s
Displays detailed network protocol statistics.
certutil -urlcache
Displays URL cache entries.
ipconfig /displaydns
Displays the contents of the DNS client resolver cache.
Event log collection
The attackers ran commands to export successful logon events for remote interactive logons (e.g., Remote Desktop Protocol) and to query those events for specific users.
Credential harvesting
Impacket — secretsdump
Attackers ran a malicious file named Adobe.exe (MD5 32a5985543433a4f60da2fafd873b927), which is a portable‑executable version of Impacket’s secretsdump.py tool. Using this tool, they extracted password hashes from domain controllers, the critical servers in an Active Directory environment. Immediately after harvesting the hashes, they issued commands to list all members of the “Domain Controllers” group, likely to identify and target additional domain controllers for further compromise.
Keylogger
Attackers dropped and executed a keylogger located at C:\Users\Public\Pictures\AnyDesk.exe (MD5: 2a571f6cee42a17d873f4c942649813f). They then created a scheduled task named AnyDesk to run the keylogger whenever any user logged on as shown below.
The keylogger creates two files: C:\Users\Public\Libraries\msect\dev0, which stores captured keystrokes, and C:\Users\Public\Libraries\msect\dev1, which holds clipboard data. Before writing to these files, the captured data is encoded by subtracting 2 from each byte.
Browser Password Decryptor
The Browser Password Decryptor tool C:\users\[username]\libraries\64.exe (MD5 37dc84e4bcad92fa28f1e7778d088283) is used to extract passwords from browsers. The tool offers two options: -help to extract passwords from Chrome and -exit to extract passwords from Firefox. For Chrome, the tool targets the Login Data and Local State databases located at %LOCALAPPDATA%\Google\Chrome\User Data\Default\Login Data and %LOCALAPPDATA%\Google\Chrome\User Data\Local State, respectively. The Local State contains the master key, which is essential for decrypting encrypted login information stored in the Login Data database file. For Firefox, the tool targets the logins.json file located at %APPDATA%\Mozilla\Firefox\Profiles\{profile folder}. The logins.json file in Firefox stores encrypted usernames and passwords for websites.
Pandora RC agent provides remote control of a victim’s computer, allowing attackers to monitor and manipulate the system. Using administrative credentials, the attacker creates a scheduled task named GoogleUpDate on the compromised machines. This task runs once with System account privileges and executes the script 1.bat, which can be found at either C:\Users\[username]\1.bat or C:\ProgramData\1.bat (MD5 5e26df131ff0a679a0a2699b723b46e3). The task’s status is first queried, then it is executed, as shown below.
The batch script 1.bat executes a command that downloads and installs the Pandora RC agent using the arguments shown below.
EHUSER: a Pandora RC user
STARTEHORUSSERVICE: start the agent after the installation finishes (default = 1)
EHORUSINSTALLFOLDER: specify the folder where you want to install the agent (default: %ProgramFiles%\_agent)
DESKTOPSHORTCUT: 0: do not create a desktop shortcut
Network scan: FSCAN
Fscan is a comprehensive internal‑network scanning tool that offers a range of functions, including network discovery, vulnerability assessment, reverse‑shell creation, and brute forcing of common services. The executable is dropped to %TEMP%\fc.exe (MD5: cf903e4a1629aa0582fd0363b5786676) and writes its output to %TEMP%\result.txt. Using Fscan, both internal and public networks were scanned to identify services running on specific ports, such as Secure Shell (SSH) on port 22 and MySQL on port 3306. The tool also attempted to access these services using credentials from the password file pp.txt.
Email harvesting
The attackers used the curl command to connect to an email server, authenticate with a username and password, and issue a command to select the Inbox folder. Typically, the goal is to:
Verify that a connection to the email server is working
Authenticate the user
Prepare the Inbox folder for reading or manipulating messages (e.g., listing, fetching, or deleting emails)
LurkProxy
In a similar manner to the OctLurk backdoor, the attacker also deployed another implant we named LurkProxy, which uses a heavily obfuscated version of the OctLurk loader. While LurkProxy has a nearly identical architecture to the OctLurk backdoor, its primary role is to proxy network traffic. Like the OctLurk, it exports a function named curl_escape_easy, which the loader invokes. Once executed, LurkProxy listens on all interfaces on hard‑coded port 64980 and establishes a TLS‑encrypted connection to the C2 server (154[.]196[.]162[.]76). The C2 communication uses a proprietary binary protocol, where each packet is compressed with zlib, encrypted with a double‑XOR scheme, and follows the structure outlined below.
Offset
Data
Type
0x00 (00)
Unused
–
0x08 (08)
Packet control flags. Bit 0 indicates high priority packet, bit 1 indicates single packet
bit array
0x0C (12)
Command number
int
0x10 (16)
Handler number (unique identifier for each proxy client in the first mode)
int
0x14 (20)
Command integer argument
int
0x18 (24)
Unused
–
0x1C (28)
Data 1 payload size
int
0x20 (32)
Data 2 payload size
int
0x24 (36)
Data 1 byte stream
bytes
0x24 (36) + N
Data 2 byte stream
bytes
LurkProxy can function as a reverse proxy in two distinct modes as described below. The mode is selected by a static flag, meaning the proxy can operate in only one mode at a time. In the implant we examined, the first (SOCKS5) mode was used.
Mode 1: SOCKS5 proxy
When a client connects, LurkProxy sends to the C2 the command 0x1000010, indicating that the connection has been established and includes the target address in the packet data. The C2 server then opens a connection to that address, enabling bidirectional communication through the appropriate commands.
Mode 2: transparent proxy
In this mode, the target address and port are hard‑coded. Upon startup, LurkProxy immediately connects to the predefined target via the C2 channel using the same command. All subsequent client connections are routed through this single, fixed target. This mode handles raw network traffic directly, bypassing the SOCKS5 layer.
Command ID
Direction
Description
Arguments
0x1000010
Implant -> C2
When a new proxy client connects, it creates a proxy session and notifies C2 of the successful configuration
Target port in command integer argument
UTF-16 encoded connection hostname in data 1
0x1000010
C2 -> Implant
Used to control the session, allowing it to pause or stop proxying
Action in command integer argument (1 to pause, or any other value to terminate)
0x1000030
Implant -> C2
Sent when the LurkProxy is shut down
–
0x1000050
Implant -> C2
Forwards the received bytes from the client to C2
Raw TCP bytes in data 1
0x1000050
C2 -> Implant
Forwards the received bytes from the proxy target to the client
Raw TCP bytes in data 1
SilkLurk
Deployment
The attacker created a service that executes legitimate binaries, such as NetSetSvc.exe (NVIDIA debug dump), nvgwls.exe (NVIDIA background tool responsible for autotuning), RtkSmbus.exe (Realtek Semiconductor’s noise‑cancelling program), and RtkNGUI64.exe (Realtek High‑Definition Audio Manager), to side‑load malicious loader DLLs: nvml.dll, vulkan-1.dll, RtkSmbusLoc.dll, and RtkNGUI64Loc.dll, respectively. These DLLs act as a loader that will inject SilkLurk backdoor into the process memory.
SilkLurk loader
SilkLurk loader working logic
The loader first verifies that it is running within the legitimate executable that loads it. Next, it moves the payload file (in the analyzed sample, it was named OneDrive.dat) from its module location (C:\ProgramData\Microsoft\Network\Connections in the analyzed sample) to the hard‑coded payload path (C:\ProgramData\Microsoft OneDrive\setup in the analyzed sample). Note that the hard-coded payload path may vary depending on the loader.
Next, the loader creates a service named RmSs to maintain persistence. The service will run the legitimate module binary (C:\ProgramData\Microsoft\Network\Connections\nvgwls.exe) that loads the malicious loader (vulkan-1.dll). The service is configured with the parameters mentioned below. Additionally, the service configuration is modified to restart the service in the event of a failure. Finally, the loader starts the service.
Service Type:SERVICE_WIN32_OWN_PROCESS
Start Type:SERVICE_AUTO_START
Error Control:SERVICE_ERROR_NORMAL
On service start, loader calls StartServiceCtrlDispatcher, which will invoke ServiceProc. The ServiceProc then calls the routine s_1800078F0_decrypt_and_run_payload. This routine computes a 32-bit hash (dword) of the victim’s computer name. The dword hash is used by a custom algorithm made up of arithmetic and logical operations to decrypt the hardcoded payload file path. The payload bytes themselves are decrypted with the same algorithm that decoded the file path. By using the victim’s computer name in the decryption of both the file path and the payload bytes, the loader becomes specific to each victim. The decrypted bytes contain shellcode with the following structure:
Shellcode offset
Description
0x000 (0)
Stub code, which performs reflective code injection
0x770 (1904)
Hardcoded value 0x11113F68, XORed with the computer name hash
0x774 (1908)
Hardcoded byte 0xD9, used as XOR key to decrypt import DLL names and APIs
0x775 (1909)
Size of the encrypted backdoor
0x779 (1913)
Encrypted backdoor data blob
The stub code decrypts and injects the backdoor blob into memory. To decrypt the blob, it first computes a dword hash of the computer’s name. This hash is then fed into a custom algorithm — a series of arithmetic and logical operations — that performs the decryption. This algorithm differs from the one used to decrypt the payload file.
The IMAGE_DOS_HEADER of the backdoor binary is zeroed out. Information in the IMAGE_NT_HEADERS, such as ImageSize and NumberOfSections, is XOR-decrypted using the hash of the computer name. The first three sections are decrypted again using a custom algorithm (a series of arithmetic and logical operations) before being injected into memory.
During import resolution, DLL names and API names are XOR‑decrypted using a hard‑coded single‑byte key. After the import DLL is loaded and the API addresses are resolved, the DLL and API name strings are zeroed out.
During relocation, the size of each relocation block, the value of each relocation entry, and the bytes to be relocated are XOR‑decrypted using the dword hash of the computer name. Afterward, the entry point is also XOR‑decrypted with the same hash and then invoked.
SilkLurk backdoor
The backdoor contains a hardcoded configuration of 0x4AC (1196) bytes, with the first 0x10 (16) bytes holding a mutex string and the remaining 0x49C (1180) bytes comprising encrypted configuration data; this configuration is written to a hardcoded filename (e.g., 2470b666bece868f, 27879a4df1a740ff) that differs across samples and is placed in the %APPDATA% directory. The configuration is decrypted using a custom algorithm involving a series of arithmetic and logical operations that is distinct from the algorithm used to decrypt the encrypted backdoor blob and payload file. The configuration has the following structure:
Offset
Description
0x00 (000)
C2 Host 1
0x64 (100)
C2 Host 2
0xC8 (200)
C2 Host 3
0x12C (300)
C2 Host 4
0x190 (400)
Port for C2 Host 1
0x192 (402)
Port for C2 Host 2
0x194 (404)
Port for C2 Host 3
0x196 (406)
Port for C2 Host 4
0x198 (408)
Unknown 21 bytes
0x1AD (429)
Proxy address 1
0x22A (554)
Proxy username 1
0x2A7 (679)
Proxy password 1
0x324 (804)
Proxy address 2
0x3A1 (929)
Proxy username 2
0x41E (1054)
Proxy password 2
The backdoor creates a TCP socket and connects to the C2 server defined in the configuration. If proxy details are provided, it attempts to establish the C2 connection through the proxy. The proxy request uses the following format:
After successfully connecting to the C2 server, it generates a random 32‑byte (0x20) network key that will be used to encrypt and decrypt network packets. This key is appended to the magic dword, as shown in the table below, creating a 40‑byte block that is then encrypted with a custom algorithm: a series of arithmetic and logical operations that differs from the one used to decrypt the configuration.
Field offset
Field size (in bytes)
Field value
0x00 (00)
0x04 (04)
0x0C7FFBE86h (magic dword)
0x04 (04)
0x04 (04)
0
0x08 (08)
0x20 (32)
Network key (will be used to encrypt and decrypt network traffic)
It then prepares a packet to send the key to the command‑and-control server, as shown in the table below. The packet contains a 0xC (12‑byte) header, a 0x28 (40‑byte) block of encrypted network‑key data (see the table above), and a randomly generated payload whose size ranges from 0x14 (20) to 0xB4 (180) bytes.
Encrypted network key data (as mentioned in above table)
0x34 (52)
size between 0x14 (20) and 0xB4 (180)
Random data bytes
After sending the key, the backdoor collects the following victim information: local computer name, DNS domain assigned to the local computer, user’s logon name, processor architecture, OS major version and build number, host IP address, current process ID, tick count value, and backdoor module name. The collected victim information is first compressed and then encrypted using the network key. The custom algorithm (a series of arithmetic and logical operations) used to encrypt collected victim information is different from the algorithms used to decrypt the configuration and encrypt the network key. Before sending the victim information, a 0x0F (15) byte header is generated and encrypted using the same custom algorithm used to encrypt the collected victim data. The header follows the format as shown in the table below.
Field offset
Field size (in bytes)
Field value
0x00 (00)
0x04 (04)
0xC7FFBE86 (magic dword)
0x04(04)
0x04 (04)
Message type (1 means victim information)
0x08 (08)
0x04 (04)
Data size (size of encrypted victim information)
0x0C (12)
0x01 (01)
Compression flag (1 means compressed)
0x0D (13)
0x02 (02)
Size of random bytes, between 0x14 and 0x96 bytes
Finally, the encrypted header and victim information are formatted as shown below and transmitted to the C2 server.
Once the backdoor has transmitted the victim information, it waits for a 0x13‑byte (19‑byte) response from the C2 server. This response follows the structure presented in the table below.
Field offset
Field size (in bytes)
Field value
0x00 (00)
0x04 (04)
Random dword
0x04 (04)
0x0F (15)
Encrypted header data
The encrypted header contained in the response is decrypted with the network key that was generated and shared with the C2 server. After decryption, the header retains the same size and structure as the one used in the victim information message.
The message type field in the header (offset 0x04) determines which operation (command) to perform. Next, the backdoor figures out the size of the command data to receive by adding up the size of the encrypted data (found at position 0x08 in the received header) and the size of the random bytes (found at position 0x0D in the received header). The received command data is first decompressed, based on the compression flag located at position 0x0D in the received header, and then decrypted using the custom algorithm that was used to encrypt the sent data. The backdoor supports the following commands:
Command (message type)
Description
03
Based on subcommand, perform the following operations:
00: Get target system’s local time
01: Set sleep time in milliseconds, after which to reconnect to the C2 server
04
Send current backdoor configuration
05
Update backdoor configuration
06
Receive and inject additional payloads (plugins) into memory. Based the on subcommand, perform the following operations:
01: Inject payload (plugin) bytes into memory and execute payload’s entry point
03: Call export method of injected plugin
Post-compromise activity
The threat actor operating the SilkLurk backdoor first used it to invoke cmd.exe to launch PowerShell. Within PowerShell, they ran commands such as net use to connect to shared network resources with administrative credentials. After establishing the connection, they searched the shared drives for confidential documents to exfiltrate. Once the search was complete, they disconnected from the network share to erase evidence of which internal servers had been accessed. To archive the stolen data, they employed legitimate archiving tools: WinRAR and 7‑Zip.
Below are the paths and names of the WinRAR and 7Zip binaries used by the attackers.
The SilkLurk backdoor opened a command shell (cmd.exe). Using this shell, the attacker executed the file C:\ProgramData\microsoft\html help\kmsonline.exe (MD5: 3c9a1ba8e0c7475706adc6376e9d7b7c). The kmsonline.exe binary acted as a dropper for the PlugX malware, deploying the malicious files listed below.
Our Kaspersky Threat Attribution Engine (KTAE) also identified a strong degree of similarity between kmsonline.exe (MD5: 3c9a1ba8e0c7475706adc6376e9d7b7c) and PlugX.
PlugX was configured to communicate with the C2 domain gycudore[.]kozow[.]com and the IP address 64[.]7[.]198[.]130. Below are the extracted configuration fields from PlugX.
Config field name
Value
Injection Target Process
%SystemRoot%\system32\svchost.exe
Home Directory
%ALLUSERSPROFILE%\Symantec
Persistence Name
SymantecRAS
Service Display Name
SymantecRAS
Service Description
Symantec RAS Services
Campaign ID
KG_MFA
Infrastructure
The threat infrastructure relies on VPS servers. Some OctLurk and LurkProxy C2 addresses are referenced in a public report by Kazakhstan’s State Technical Service (STS) company. According to available data, a campaign targeting critical infrastructure in Kazakhstan was discovered in March 2025. During this campaign, attackers employed the TrustFall (STS internal designation) remote access malware, also known as MystRodX (Qianxin) and SilentRaid (Cisco) and designed for Linux-based operating systems. Subsequently, in October 2025, STS researchers found additional TrustFall samples, while also discovering its new C2 servers via active probing. Notably, three observed TrustFall C2 addresses were also leveraged by OctLurk and LurkProxy. This overlap points to shared infrastructure across multiple OS-targeting campaigns, though it remains unclear whether these activities ran concurrently or at different times.
Attribution
We identified multiple artifacts confirming that OctLurk and SilkLurk are operated by the same threat actor. Several users infected with OctLurk were also found to be infected with SilkLurk, and in some cases both malware families used the same staging directory. Below are examples of these artifacts.
In one incident, the attackers created the service C:\Windows\system32\svchost.exe -k ExAstSrc -s ExAstSrc to deploy OctLurk. They used OctLurk to obtain a command shell and were observed dropping the SilkLurk loader vulkan-1.dll (MD5 be4731c09734da2e8eb6814a9c82f266) via this shell, as shown below.
In another incident, we observed attackers using the same directory C:\ProgramData\intel\ to drop both the OctLurk and SilkLurk loader DLLs.
In one incident, the attacker used SilkLurk to obtain a command shell (cmd.exe) and then deployed and executed the PlugX malware. The PlugX sample was configured to contact gycudore[.]kozow[.]com as its command‑and‑control (C2) server, while the SilkLurk backdoor used ctyuhjerf[.]kozow[.]com for C2. PlugX is a well‑known modular remote‑access Trojan (RAT) that has been active since at least 2008 and historically linked to Chinese-speaking threat actors. This suggests that both OctLurk and SilkLurk were also developed and operated by a Chinese‑speaking actor, although at this time, we cannot attribute this activity to a known threat group.
Conclusions
The emergence of the OctLurk and SilkLurk multi‑plugin malware framework highlights how threat actors continuously refine their tactics to evade detection and maintain control over compromised networks. Both families operate primarily in memory, leaving only a minimalistic loader on disk that relies on machine‑specific data (OctLurk uses the drive serial number, and SilkLurk uses the computer name) to decode payload locations and contents. This victim‑specific encoding makes reverse engineering and automated detection considerably harder.
In addition to sophisticated obfuscation, the attackers establish redundant access channels, harvest credentials, and deploy well‑known remote access and monitoring tools. These secondary pathways ensure persistence even if the original infection vector is discovered or neutralized.
How the Attack Operates Threat actors are quietly hijacking hotel Wi-Fi gateways to reroute traveling executives to fake Microsoft 365 login pages, stealing corporate credentials without leaving a trace in...
In February 2026, we discovered a set of malicious activities that had been ongoing since late 2025. These activities involved a RAT module written in Go with proxy capabilities, which served as the main stage of the attack. The attack targeted government and diplomatic entities in Southeast Asia and showed a level of sophistication that caught our attention.
During the attack, the main malware, dubbed GoSerpent, received an encrypted argument and started communicating with a remote server. It was also used to deploy further malicious tools to collect sensitive data and dump credentials on the system.
Monitoring the activities of this threat actor revealed that in May 2026, they came back with an evolved set of malicious tools: a new RAT and proxy tool, Stowaway, which resembled the initial malware, as well as an additional stealthy tool to exfiltrate sensitive data collected in the previous few months through network shares.
We found earlier versions of the GoSerpent backdoor used since 2021 against victims in Southeast Asia with relatively simpler code that received command-line arguments in plain text. Even though the newer variant is stealthier, the attackers continued using the simpler version alongside the latest one in their recent attacks.
What makes this threat particularly concerning is the strategic deployment of various tools with sophisticated data collection and exfiltration capabilities.
In this article, we introduce the malicious tools uncovered by us, which have been used since late 2025.
Technical details
Initial phase of the attacks
The initial phase of the attacks involved deployment of the GoSerpent backdoor, followed by additional malicious tools. During this phase, the main goal was to collect sensitive files and store them for future exfiltration, which was done by a data collecting tool, ThumbcacheService. The attackers also needed system credentials to exfiltrate the collected data through network drives at a later stage. This was achieved through a number of credential dumping tools deployed in this phase via the GoSerpent backdoor.
GoSerpent backdoor
The primary weapon in this campaign is the GoSerpent backdoor, a sophisticated Go-based remote access Trojan that has been active since at least 2021, with the most recent variant deployed in 2026.
This malware receives encrypted and base64-encoded command-line arguments containing a C2 server address and communication password, which are decrypted using AES-CBC mode with a fixed IV (31323334353637383930616263646566) and keys derived from predefined strings.
The backdoor connects to command-and-control servers using ChaCha20 encryption for communications, with the SHA256 hash of the communication password serving as the encryption key.
GoSerpent supports multiple C2 commands by receiving special command values. The commands include the following:
Command
Symbol (as derived from corresponding function names)
Description
2BA1
Sync
Respond to the server to show the infection is active
3BA2
Exit
Exit process
4BA3
Ls
Start listening on a port
5BA4
Connect
Connect to a remote server
6BA5
Hello
Create a shell on the infected machine
7BA6
Ul
Upload a file or directory to the server
8BA7
Dl
Download from the server
9BA8
Ss5
Start a SOCKS5 proxy on the infected machine
ABA9
Cl
Close a listening port
CBAB
RF
Forward to a connected node
GoSerpent can establish SOCKS5 proxy servers to route traffic through compromised hosts, enabling attackers to access other networks while masking their true IP addresses. The backdoor is capable of deploying additional malicious tools, including ThumbcacheService for file collection, Mimikatz for credential dumping, and QuarksDumpLocalHash for local account password hash extraction. The malware exhibits strong persistence mechanisms and uses filenames that mimic legitimate system processes such as lass.exe and updates.exe to evade detection.
McMx RAT
McMx is a basic Go-based proxy and remote access tool that represents a simpler variant of the GoSerpent backdoor, apparently compiled from a different GitHub repository path.
Unlike the latest variant of GoSerpent, which uses encrypted command-line arguments, McMx receives input parameters from text files in plaintext format — in a way that resembles older versions of GoSerpent. The malware features similar function names with apparent typos present in both tools.
Before executing McMx, attackers manipulate batch files to generate configuration files containing C2 parameters. The patterns observed show the use of echo commands to create configuration files with parameters like remote host addresses, ports, and secret keys. The McMx malware is then deployed with this configuration.
The tool shares core functionalities with GoSerpent, including:
SOCKS5 proxying
port forwarding
file transfer
remote shell capabilities
Data collection and credential dumping tools
Following initial deployment of the GoSerpent backdoor, attackers typically wait several days before utilizing it to download and execute additional malware components for data collection and credential dumping.
ThumbcacheService
ThumbcacheService is a malicious DLL deployed as a Windows service that functions as a sophisticated file collection mechanism within the GoSerpent ecosystem. The malware employs XOR encryption with a single-byte key of 0x13 for string obfuscation. It decrypts embedded strings and creates a database file named thumbcache_605a.db in the C:\Users\Public\ directory to store collected sensitive files. It specifically targets documents with the following extensions: .doc, .docx, .pdf, .xls and .xlsx.
The targeted files are then archived using 7-Zip and protected with a predefined password @vx0a9n5W2M0c3D6.#, enforcing a 20MB size limit for archives.
The malicious service also monitors the $Recycle.Bin directory for deleted files with the extensions of interest, ensuring comprehensive data collection.
Credential dumping tools
The threat actor deploys the following tools via GoSerpent backdoor to dump credentials:
Mimikatz — dumps memory from the LSASS process to extract credential material, including cached credentials and Kerberos tickets.
QuarksDumpLocalHash — extracts local account password hashes from the SAM registry hive, allowing for offline password cracking attacks.
These tools work together to maximize information extraction from compromised systems. The stolen credentials were used in later stages of the attack to facilitate the exfiltration of sensitive files collected by ThumbcacheService.
Second stage of the attacks
After the initial phase of the malware deployments, the attackers allowed a few weeks for the ThumbcacheService to silently collect sensitive files without exfiltrating them. In the meantime, the credential dumping tools also continued to steal credentials. In May 2026, the threat actor came back with a set of new tools. The main malware of this round of activity was another Go-based RAT and proxy tool, Stowaway. It was used to deploy the two-stage data exfiltration tool TmcLoader/TmcPayload, which was the last piece of the data theft puzzle.
Stowaway
Stowaway is a proxy and remote access tool compiled from an open-source framework with customized functions to make the infection stealthier. This malware features both network admin and agent capabilities, enabling attackers to establish chained proxy paths across multiple hosts with the following functionalities:
SOCKS5 proxying
port forwarding
reverse tunneling
remote shell access
file transfer
SSH-based tunneling
Communications are transported over TCP, HTTP, or WebSocket channels protected by AES-256-GCM or TLS encryption.
As the next step, the attackers deliver two files to the victim machine via Stowaway:
TmcLoader with an embedded payload
{BBF061R2-BE25-4F6D-8B2D-1A6A39C3FSA2}.db — an encrypted configuration file
TmcLoader/TmcPayload
TmcLoader is a stealthy C++ loader module registered as a Windows service. The malware embeds an encrypted payload dubbed TmcPayload within its .data section, which is decrypted and loaded into the memory space of the svchost process to maintain persistence and avoid detection.
TmcLoader employs dynamic API resolution through a circular XOR encryption, where each byte is XORed with the value of the subsequent byte, combined with Base64 encoding for string obfuscation to hide API names.
The loader creates a unique event to prevent multiple infections on the same system. After that, it extracts and decrypts the embedded TmcPayload. This payload component is responsible for exfiltrating sensitive data from the victim’s machine.
TmcPayload generates a file path from an obfuscated string:
C:\Users\Public\Libraries\{BBF061R2-BE25-4F6D-8B2D-1A6A39C3FSA2}.db.
It then checks for the existence of this configuration file. If the file doesn’t exist, it delays execution for a random period of time before rechecking. The configuration file contains encrypted network share credentials and destination paths for data exfiltration. It specifically references the thumbcache_605a.db file created by ThumbcacheService as the file to be exfiltrated, demonstrating the integrated nature of the attack chain.
Toolset integration
What distinguishes this threat actor’s approach is the deliberate integration between different components of their toolset. The chain from ThumbcacheService to TmcLoader/TmcPayload demonstrates sophisticated operational planning:
ThumbcacheService: deployed via GoSerpent, collects and archives sensitive files into the thumbcache_605a.db database file.
Credential dumping tools: deployed via GoSerpent to retrieve system credentials.
Configuration file: delivered via Stowaway, contains credentials and file paths for data exfiltration.
TmcLoader/TmcPayload: deployed via Stowaway, reads the configuration file for data exfiltration.
Data transfer: using network credentials and destination paths from the configuration file, TmcPayload transfers the exact same thumbcache_605a.db.
This integration shows that the threat actor has carefully orchestrated their tools to work together seamlessly, ensuring that data collected by one component is available for exfiltration by another component.
Infrastructure
The malware operators leverage legitimate hosting providers, including Alibaba Cloud and UCLOUD HK, for their command-and-control infrastructure. The use of legitimate hosting platforms demonstrates operational security awareness, making detection more challenging.
The technical similarities between GoSerpent and the newer Stowaway tools strongly suggest the threat actor’s deep familiarity with network proxy technologies. The consistent use of legitimate domain names as secret keys, with GoSerpent employing www.microsoft.com and www.spacex.com and Stowaway utilizing github.code, indicates a standardized operational methodology.
Attribution
While the exact attribution of the GoSerpent campaign remains uncertain, there are indications of a potential link to the TetrisPhantom threat actor. The similarities in victim targeting, technical capabilities, and operational methodologies suggest a possible connection. However, further investigation is necessary to confirm this association.
Conclusion
The GoSerpent campaign represents a sophisticated and evolving threat to government and diplomatic entities in Southeast Asia. The threat actor’s use of customized tools, such as the GoSerpent backdoor, Stowaway, and TmcLoader, demonstrates a high degree of technical expertise and operational planning. The integration of these tools to collect and exfiltrate sensitive data highlights the actor’s focus on long-term access and intelligence gathering. As the threat landscape continues to shift, it is essential for organizations to remain vigilant and implement robust security measures to detect and prevent such attacks. By understanding the tactics, techniques, and procedures (TTPs) employed by this threat actor, defenders can better prepare themselves to counter similar threats in the future.
In January 2026, we identified multiple attacks involving unknown malware that captures the contents of cryptocurrency wallet windows. During the investigation, we reconstructed the complete infection chain, which consisted of four tightly linked stages initiated by the execution of the previously described malicious PowerShell script TookPS. However, this campaign differs from previous activity in that it uses a new framework to deliver all malicious modules and orchestrate them via an SSH tunnel. In total, the framework includes more than 20 malicious payloads and implants, covering a wide variety of functions. At the time of writing, the threat remains active.
Kaspersky’s products detect this threat as Trojan-Downloader.Win32.TookPS.*, Trojan.Win64.BypassUAC.*, Trojan-Banker.Script.Agent.gen, Trojan.Win32.Dllhijack.*, Backdoor.Win32.TeviRat.*, Trojan-PSW.Win64.Stealer.*, Trojan-Spy.Win64.Keylogger.*, Trojan-Spy.Win64.Agent.*, Trojan.Win64.Agent.*.
Background
TookPS is a downloader used for retrieving malicious commands and scripts from attacker-controlled servers to further propagate attacks. The first campaign using TookPS was discovered in March 2025. At that time, malicious scripts delivered a Python‑based infostealer along with a script that installed and configured an SSH tunnel on the victim’s machine. The next wave appeared in April 2025: the payload was changed, and TookPS was used to deliver the TeviRAT malware with the same SSH installer.
Then at the end of April 2025, TookPS underwent minor changes, yet its attack chain was completely redesigned. Unlike previous incidents, in this case, TookPS was used solely for the initial infection, with an automated SSH bot responsible for payload delivery. This new malicious campaign has multiple stages that cover the full attack lifecycle, from initial infection to persistence and data exfiltration. Among various malware strains, at one of the stages, the TeviRAT backdoor is delivered to the compromised host, ultimately fetching another version of a TookPS script.
We dubbed this updated TookPS campaign “OkoBot”.
Original OkoBot infection chain
We will break down this chain in greater detail later in the article. However, this is not the only version of OkoBot we were able to find. Already in March 2026, we discovered a new phase in the development of the framework, with Volume2 now being installed directly using TookPS. The HDUtil launcher → extl injector → Rilide chain was found to be abandoned in this newer version since it was replaced in full by the identical ext_daemon Volume2 plugin. TeviRAT was also removed, most likely because its functions were covered by the new plugins dispatcher.
New OkoBot infection chain
Initial infection
The initial infection is primarily delivered through two vectors: a ClickFix attack, and malware distributed through GitHub that masquerades as legitimate software. One such example is the fake SQL Server Management Studio (SSMS) package distributed through GitHub. In fact, it is actually the legitimate Audacity — a popular audio editor — compiled with a malicious implant embedded in one of its libraries. Because the repository was indexed by most search engines and appeared at the top of the results for the query SSMS, the malware looked legitimate and quickly earned users’ trust.
Malicious application distribution report
This repository was created at the end of March 2025 and existed until June of that year. It consisted of a single file, README.md, which provided a fake SSMS installation guide written in an official style and likely derived from excerpts of Microsoft’s documentation. However, the download link for the program, located at the beginning of the guide, pointed to the latest release in the same repository.
Both infection vectors trigger the execution of the malicious script TookPS, which installs SSH on the victim’s system, establishes a connection to the attacker-controlled SSH server and subsequently forwards the SSH daemon port. Following a delay, an automated SSH bot connects to the forwarded port.
Back connection
The automated SSH bot collects system information such as usernames, antivirus software installed, the IP address, and OS version. It harvests cryptocurrency wallet files, browser cookies, profiles, and other credentials through an SSH tunnel. For subsequent delivery of malicious modules, it disables Windows Defender notifications via a registry modification. Moreover, it gains access to the graphical session on the victim’s system using the following sequence:
Open firewall ports for inbound RDP traffic
Create a user in the “Remote Desktop Users” group
Replace the legitimate termsrv.dll with a patched one to permit multiple concurrent RDP sessions
Create a scheduled task named Apple Sync to maintain a reverse SSH tunnel that forwards the local RDP port every hour
After that, the SSH bot begins retrieving malicious modules over SFTP.
Launcher with advanced options
One of the deployed modules is HDUtil, an auxiliary utility protected with VMProtect and heavily obfuscated. This launcher is used by the SSH bot during an attack to deploy various malicious modules via the target command. Additionally, it implements three auxiliary commands that were not observed during the attacks we analyzed. Nevertheless, their presence and potential capabilities further demonstrate the high degree of integration among all components of the framework.
Active sessions
At startup, the launcher verifies its execution environment by checking the HWID in the contents of %PROGRAMDATA%\hwid.dat, a technique consistently employed throughout the framework. If the file is missing or contains invalid data, such as a non‑MD5 hash, the launcher terminates without performing any further actions. Otherwise, the specified commands are executed. For example, enumsessions provides a list of sessions along with detailed information, including the session type (Console, Services, RDP, and others), username, connection host, and domain. In turn, enumadapters returns the names of all graphics adapters present on the system.
Example output of HDUtil enumeration commands
UAC bypass
The most important command of the launcher is target, which enables payload execution on the system. An optional nouac argument enables automatic UAC bypassing via Windows RPC and an auto-elevated msconfig.exe program, allowing the payload to run with elevated privileges stealthily. This technique has been known for a long time, discovered and described in 2019 by the Project Zero team, who provided a full report with a detailed technical description.
Below is the list of all HDUtil commands.
Command
Description
target [nouac [user=<user>]] [noattach] <file>
Starts file and prints its output.
If optional argument noattach passed, command to be executed in background.
If optional argument nouac passed, automatic UAC bypass to be performed.
If optional argument user passed, new process to be executed under , otherwise default local administrator to be chosen.
pcopy <file> <dir_src> <dir_dst>
Copies file <file> located in <dir_src> to <dir_dst>. Not used by SSH bot.
enumadapters
Prints names of graphical adapters on current system. Not used by SSH bot.
enumsessions
Prints all sessions on current system. Not used by SSH bot.
Browser extensions loader
The first malicious module delivered to the infected system via SFTP is executed using the previously described launcher with the command .\HDUtil.exe target extl.exe. It is a heavily obfuscated DLL injector protected with VMProtect. At startup, the module enters an infinite loop and uses the EnumWindows and IsWindowVisible API methods to enumerate the PIDs of active windows and retrieve the corresponding executable filenames. For processes associated with widely used Chromium‑based browsers, the module invokes a routine that injects a specialized implant.
The injector opens a process, allocates a memory region, and writes the payload directly into this region as unencrypted raw bytes. Then it resolves two exported implant functions, LdrInitMain and LdrCallMain, based on a pre-specified hash derived from a modified version of DJB2 hash function. The first function performs the final PE unpacking, including rebase operations and the initialization of the import and exception tables. The second function directly initiates malware execution.
Setting up protections on the regions and launching the implant
This loader installs malicious browser extensions and hides them from the user. It uses an internal engine that resolves the addresses of stripped functions by analyzing the byte patterns of their calls using YARA-style syntax. This approach enables the malicious code to access critical Chromium engine functions required for extension installation and management. This functionality is also implemented for other browsers with appropriate modifications. For example, in the case of Microsoft Edge, the corresponding DLL msedge.dll is hooked using the specific patterns.
List of the functions hooked by the malware
Using the obtained address of the BrowserProcess object, the loader traverses the inheritance hierarchy and subsequently resolves a pointer to the function responsible for registering observers of browser‑window creation, specifically ProfileManager::BrowserListObserver::OnBrowserAdded. With a specialized built‑in engine, they are hooked using the attacker’s own implementations while preserving the original function’s address.
The loader replaces the functions it finds with its own
When a new Chromium window is opened, a hooked function is invoked that silently installs extensions. This routine scans the user’s %APPDATA% directory, loads all .crx files (Chromium-based browsers extension format), and records them in the ext_table. The extensions are then installed in the browser.
During installation, the extension is unpacked into a non‑default extensions directory, Local Extension Settings, and its manifest is dynamically modified. An object named custom_args is added, containing the fields hwid (the identifier of the infected system) and browser (the name of the browser in which the extension is installed). Then, using previously resolved internal functions of chrome.dll, the extension is installed and all requested permissions are granted.
Extensions are unpacked into a non-default directory
All extensions loaded in this manner are added to a special array to be subsequently identified among regular extensions and to remain hidden from the user.
The remaining patched functions are used to hide the installed malicious extensions from the user. When invoked with registered extensions as parameters, they perform no operation and return a constant value. This enables the threat actor to suppress notifications related to the malicious nature of the extensions and to exclude them from the displayed list of installed extensions. As a result, the behavior of other extensions remains unaffected.
Stub for hiding malicious extensions
During the attack, the Rilide extension was installed on the victim’s system using the previously described loader. Rilide is a stealer targeting Chromium-based browsers that has been frequently used by Russian-speaking threat actors since April 2023. The malware is designed to steal sensitive user data, including login credentials, cookies, and financial information, with a specific emphasis on cryptocurrency theft.
Plugins dispatcher
The final module delivered via SFTP is an open-source utility called Volume2, which is executed with elevated privileges using the command .\HDUtil.exe target nouac noattach Volume2.exe. The executable was linked with the malicious protobuf.dll library. Although the library seems identical to the legitimate DLL, it has been modified to include a malicious exported function, ProtobufGetVer2. This function decrypts and initiates a malicious implant. The payload is encrypted using AES GCM, initialized with a static 256‑bit key and a 96‑bit nonce. The GCM authentication tag is omitted, resulting in the absence of integrity verification. Starting in March 2026, the name of protobuf.dll was changed to version.dll, although its contents remained a modified ProtoBuf library.
Decrypting implant using AES GCM and subsequent mapping
The loaded implant functions as a malicious plugin dispatcher. Upon initialization, it reads and verifies the HWID before establishing communication with the C2 server via the HTTP protocol. Each request follows a predefined binary format: a 2-byte numeric bot identifier encoded in little-endian format, followed by an AES CBC-encrypted JSON object. By default, the BotID is set to 0, and the key and IV consist of 32 and 16 bytes of 0xff, respectively. The implant polls the server every 20 seconds to retrieve new commands. The request contains client data encoded in Base64, and the server may respond with a command containing three mandatory fields: TaskIndex (the command number from the dispatcher), TaskID (a unique task identifier), and HWID (the client identifier). The dispatcher supports four built-in commands:
Task index
Action
1
Reconfigure client: update session keys, assign ID, switch to another C2
2
Load DLL implant into memory and run its entry point
3
Load plugin into process and register tasks with RegisterPlugin function
4
Restart dispatcher as new process
x
If the task number is none of the above, search for it among the registered plugins
Each plugin is required to export two functions: RegisterPlugin and PluginDispatch. These functions are used to manage and configure plugins. The RegisterPlugin function registers the plugin’s tasks with the dispatcher, whereas the PluginDispatch function is invoked when the plugin is called. Both these functions, as well as other external API functions, are located within the base libraries using one algorithm. This algorithm iterates through the export table and uses a specialized callback that calculates the MurmurHash3 hash and compares it against the target value to identify the appropriate function.
Resolving a plugin initialization function
During the analysis, we were able to discover five plugins that implement functions under their unique task identifiers.
CMD wrapper (10xx): allows running scripts and individual commands in cmd.
PowerShell wrapper (11xx): allows running scripts and individual commands in PowerShell.
Environment enumerator (12xx): gathers system information, active sessions, and processes.
Dropper (14xx): downloads an additional payload directly onto the system both from embedded Base64-encoded binary blob and via URL.
Process injector (16xx): launches additional malicious implants on the target system by injecting them into legitimate processes.
We identified four malicious implants that are delivered to the system via the process injector plugin.
ext daemon
The malware is functionally identical to the browser extensions loader (extl.exe) described above, but less obfuscated and not protected with VMProtect.
SeedHunter
Similarly to extl.exe, this malware monitors the list of active processes in the system and injects an implant into Trezor Suite, Ledger Wallet, and Ledger Live processes. The implant is malware that collects seed phrases of Ledger and Trezor cryptocurrency wallets. Initially, it verifies the HWID, and if it fails, it terminates immediately. Then, based on the value of BaseDllName, the malware determines the process context and uses the corresponding implementation for either Trezor or Ledger. It then utilizes the previously described technique to hook the internal Electron framework functions.
List of functions hooked by the malware
Then the malware communicates with the C2 (moonsand[.]store) over HTTPS, sending a Base64-encoded JSON request containing the fields Pid, HWID, and Build. In response, it receives a JSON payload containing the Wait flag. If this flag is set to true, the malware initiates periodic USB device scans filtered by VID and PID (Vendor and Product ID). Upon detecting a connected Trezor or Ledger hardware wallet, it invokes the hooked functions to display a hard‑coded phishing page designed for seed phrase recovery, with a distinct layout used for each identified wallet. If the Wait flag is set to false, the phishing page is displayed immediately.
When the seed phrase is entered and validated, the JavaScript code of the page outputs the phrase to the console prefixed with @:app:print. This prefix helps identify the malware messages in the hooked function mal_LogConsoleMessage.
Phishing pages for seed phrase recovery
The obtained seed phrase is subsequently sent to the C2 server within a JSON payload containing fields such as App (ledger or trezor), Build, DeviceName, DeviceHardwareId, and SeedData. Furthermore, an identical JSON, encrypted with the RC4 algorithm using the HWID as the key, is saved in a temporary directory under the filename sh_<ts>.json, where <ts> is the file creation timestamp.
MC Keylogger
This module is a keylogger that, in addition to recording user input, performs three malicious activities:
Clipboard logging: periodically checks various clipboard formats, including CF_HDROP for files dragged between windows, CF_DIB for copied bitmap images, and CF_UNICODETEXT for Unicode text. Each format is handled appropriately, and all copy events are logged under the Clipboard section. Text data is written directly to the log, while copied files are recorded by their file paths. Images are saved as JPG files following the naming pattern bf_YYYY-MM-DD hh_mm_ss.jpg, and the path to the saved image is added to the log.
Logging connected devices: logs information about USB devices connected to the system, including hardware characteristics like VID, PID, manufacturer, and other details.
Screenshot creation: creates a screenshot every five minutes with a name in the format sc_YYYY-MM-DD hh_mm_ss.jpg. A corresponding message is recorded in the log under the Screenshot section, including the path to the screenshot.
Thus, the keylogger creates three types of different file artifacts, which are placed in a temporary directory. Below is an example of a log file generated by the keylogger.
Example of the keylogger log file
OkoSpyware
This module, which we dubbed OkoSpyware, captures both keystrokes and the video stream of the target application’s window. It first compiles a list of over 100 executable names, including cryptocurrency wallet applications (such as Exodus or Litecoin QT), password managers (such as KeePassXC or 1Password), and other widely used applications, to identify which processes should be monitored among all active system processes. For each identified process, the module uses a bundled FFmpeg instance to capture an MP4 video of the window while concurrently logging keystrokes within that window. The resulting video file is saved in %TEMP% as media_<ts> (where <ts> is the recording’s start timestamp). In the same folder, a JSON file named oko_<ts>.json is created, containing metadata about the captured stream, such as the process name, intercepted input, the stream’s MD5 hash, and additional details.
Example of an OkoSpyware metadata file
The malware also monitors the state of browsers, and when the window title matches a specified regular expression — for instance, a MetaMask or Tonkeeper wallet extension page — it performs video recording and input logging, adding the window title value to the corresponding field in the JSON metadata file.
Artifacts exfiltration
The TookPS script launched via a scheduled task receives a PowerShell exfiltration script as its payload from the C2. All files created by the MC Keylogger and OkoSpyware are sent to the C2 server to the endpoint ir-post.php. After that, the files are deleted from the victim’s system and a command history file, ConsoleHost_history.txt, is cleared.
Sequential exfiltration of artifacts from the temporary directory
Victims
At the time of writing, we have detected hundreds of victims of the OkoBot campaign in more than 25 countries, with the largest proportion of attacked end users found in Brazil, Vietnam, Canada, Mexico, and Türkiye.
Distribution of users attacked by OkoBot by country, April 2025–June 2026 (download)
Attribution
At the time of writing, we can’t attribute this malicious campaign to any known crimeware actor. However, during the analysis, we observed that the servers hosting the PowerShell scripts used in the initial infection stage implement server-side geoblocking. When attempting to retrieve the malicious script using an IP from Russia or CIS countries, the server returns an empty response. This technique is very popular among Russian-speaking threat actors.
It was previously mentioned that the campaign uses the malicious Rilide extension, an infostealer that is actively spreading on Russian-speaking, invitation-only cybercrime forums. Additionally, the source code of the SeedHunter phishing pages includes comments in Russian.
Conclusion
The framework described here has numerous modules — mostly written in C and C++ — that are obfuscated and use a variety of packing techniques. Across all stages, specific patterns and techniques can be identified that are borrowed and used in other modules, which allows us to conclude that there is a close interconnectedness among all stages, forming a full‑fledged high‑level framework. Overall, these modules enable a wide range of functions, such as collecting local files, executing remote commands, downloading arbitrary browser extensions, and stealing crypto wallets.
The OkoBot campaign has been ongoing for over a year, and it remains active at the time of publication. Moreover, it is adapting, which indicates that this framework is being maintained and distribution campaigns continue.
We continue to share details on the malicious techniques and toolsets used by the ToddyCat APT group. In the first part of this report, we examined the group’s attacks aimed at stealing data from browsers, as well as from local and cloud email services. The methods used in that campaign indicated that ToddyCat was attempting to access corporate correspondence while evading monitoring tools. However, all of the group’s methods we described previously are effectively detected by EPP and EDR solutions.
The attackers continued their search for ways to bypass security solutions and developed a new tool to gain access to a victim’s cloud account via the Google API. Armed with this tool, the group automated all stages of the attack and managed to remain undetected by monitoring systems.
In this part of the report, we break down the mechanics of this new attack and analyze the tool that was used to automate it. We’ll also discuss how to detect and defend against this threat.
Umbrij
In this campaign, the attackers focused their attention on corporate email communications hosted on Gmail, targeting access compromise via APIs. Because the Google API relies on the OAuth 2.0 protocol for authorization, applications can use an OAuth token to access requested email resources. To acquire this token, the threat actors developed a tool called Umbrij and used it to connect to the browser’s management console in headless mode via a remote debugging port. Through a series of requests, they obtained an OAuth authorization code, which they subsequently exchanged for an access token to reach the target resources via the API. We have dubbed this technique Shadow Token via Remote Debug (STRD).
This attack is viable on Chromium-based browsers. If the user has not logged out of their Gmail account, the browser maintains an active session. The attackers exploit this: they launch the browser, connect via the remote debugging port to take control, and send a request to the Gmail service to grant access to the Google account resources within the context of the user’s saved session.
During our investigation of this attack, we discovered several versions of the Umbrij tool. These versions included a variety of helper functions designed for debugging, as well as for searching and selecting user accounts within the browser, among other tasks.
Kaspersky solutions detect this tool with the following verdicts: HEUR:Trojan-PSW.MSIL.Umbrij.gen, HEUR:Trojan.MSIL.Agent.gen, HEUR:Trojan-PSW.MSIL.Agent.gen.
Execution
The Umbrij tool was discovered during a proactive threat hunting operation: a scheduled task, KasperskyEndpointSecurityEDRAvp, was running on a user host, launching a digitally signed file. Kaspersky solutions do not create scheduled tasks with that name; the attackers were attempting to masquerade their malicious activity as a legitimate process.
The signed file then used the DLL sideloading technique to load the malicious tool.
Umbrij execution events within Kaspersky Managed Detection and Response
Throughout our observation period, we identified the following legitimate files vulnerable to the DLL sideloading technique that were used to launch Umbrij:
BDSubWiz.exe: a component of the Submission Wizard in Bitdefender ConnectAgent, which is used to support connection features and interaction with other Bitdefender services or agents. This file insecurely loads a file named log.dll.
VSTestVideoRecorder.exe: a component of the video-recording tool used for testing with Visual Studio (VS Test). This executable insecurely loads a file named Microsoft.VisualStudio.QualityTools.VideoRecorderEngine.dll.
GoogleDesktop.exe: the discontinued Google Desktop Search application for indexing files and performing quick searches on a local Windows computer. This executable insecurely loads a file named GoogleServices.dll.
These files were used to load different versions of Umbrij; the same legitimate file could be leveraged to launch more than one variant. In total, we discovered three versions of Umbrij, which we refer to as a, b, and c for convenience.
The tool itself is a DLL written in .NET and obfuscated with ConfuserEx, an open-source obfuscator for .NET applications.
Example of an obfuscated code snippet
Umbrij is managed with the help of parameters passed through a command line at startup, although it is occasionally executed without any parameters. Below are examples of the command lines observed in attacks against users:
However, these are not the only parameters the tool can accept and process. During the analysis of its executable code, we discovered additional parameters that vary depending on the version of Umbrij. See the table below for the parameters and their descriptions.
Version
Command
Description
a
-regex <string>
Used in conjunction with the -deepsearch parameter. Specifies a substring to search for within the user_name field of the user profile file, which typically contains the email address. The tool will utilize the user profile that matches this specified substring
a
-user <username>
Specifies the system username under which the tool will run
a
-runas-currentuser
Configures Umbrij to run within the execution context of the current user
a
-deepsearch
Enforces additional checks on the user_name field in the user profile: verifying that it is not empty and that it contains the substring specified in the -regex parameter
a, b, c
-path <path>
Specifies the full path to the directory containing the browser’s executable file
a, b, c
-browser <both|msedge|chrome>
Specifies which browser the tool should target: Google Chrome, Microsoft Edge, or both
a, b, c
-debugport <port>
Specifies the remote debugging port number
a, b, c
-sync
When this parameter is specified in the URL, the value 1095133494869 replaces 279448736670 in the permission request
b
-domainAd
Specifies the domain name if the user account is a domain account
b
-savepdf
Instructs Umbrij to save a screenshot of the user profile as a PDF file
c
-lport
Same as debugport
Environment preparation
At startup, the tool evaluates several prerequisites required to carry out the attack and performs preparatory actions to subsequently compromise the Gmail account.
First, Umbrij verifies the availability of the port that will be designated for browser debugging. To accomplish this, the tool utilizes a function named ChekPortAvailable() (original spelling retained), which accepts the target port number as a parameter. It then retrieves information about active connections on the host using the .NET GetActiveTcpConnections() function from the System.Net.NetworkInformation namespace. The tool iterates through each connection in a loop, comparing the port number to the one it is checking.
The ChekPortAvailable function used to verify open ports
After this, the tool retrieves the user context. It searches the system for the explorer.exe process and duplicates its token, retaining all of its privileges (T1134.003 Access Token Manipulation: Make and Impersonate Token). This is the exact same mechanism used by another tool in the group’s arsenal, TomBerBil, which we covered previously.
The ImpersonateWithProcess function used to retrieve user context
By default, Umbrij duplicates the token of the first explorer.exe process it encounters. If multiple users are logged in to the system, the -user <username> switch can be used to specify the name of the target user whose token to duplicate. If the -runas-currentuser switch is specified, the tool will execute within the context of the current user without duplicating any tokens.
Next, Umbrij constructs the path to the browser application folder within the user’s local application data repository. To do this, it uses the Environment.SpecialFolder.LocalApplicationData command to retrieve the repository directory from the environment variable and appends the directory of the target browser. The tool then searches for the Local State file in the following folders:
%LOCALAPPDATA%\Google\Chrome\User Data\Local State
%LOCALAPPDATA%\Microsoft\Edge\User Data\Local State
See below for an example of the Local State file structure.
Structure of the Local State JSON file
Within this file, the tool searches for the info_cache array, which stores information about browser user profiles. Umbrij enumerates all user profiles and looks for those containing a user_name field that includes an email address. The presence of an email address indicates that the user is authenticated to a Google service. While the tool can interact with every profile it finds, if the -regex <string> parameter is passed through a command line, it searches for the specified substring within the email addresses being enumerated and proceeds exclusively with those matches.
Next, Umbrij creates the following directories for Google Chrome and Microsoft Edge, respectively:
%LOCALAPPDATA%\Google\Chrome\BackupFiles\
%LOCALAPPDATA%\Microsoft\Edge\BackupFiles\
The tool copies the following user files and folders of each target user profile into these directories:
IndexedDB: a folder containing a relational database used for client-side storage of structured data
Local Storage: a component of the browser’s web storage that provides a key-value mechanism for storing data on the client side
Network: a folder where the browser stores files related to network requests and caching, such as the network cache and session files
Login Data: a file that stores saved passwords for various websites and applications
Login Data For Account: a file that stores credentials associated with a Google account or other synchronized accounts within the browser
Preferences: a file containing profile-level browser settings
Secure Preferences: a file that stores protected configurations, such as security and synchronization data
Web Data: a file that stores auto-fill data
If these files are locked by other processes, the tool includes a dedicated function to force-copy them.
The ForceCopyFolder function used to copy files locked by other processes
As the next step, the tool searches the “Program Files” and “Program Files (x86)” directories for the browser installation folder. Once it locates the executable file and successfully copies all required files, it is ready to proceed with acquiring the authorization code.
Acquiring the authorization code
In the next phase of execution, Umbrij launches Google Chrome, Microsoft Edge, or both browsers sequentially, depending on the parameters passed in the command line. It then passes arguments to the browser based on the following template:
It populates the template with the following values:
{0}: the path to \BackupFiles\, where the user profile files were copied
{1}: the path to the browser executable file
{2}: the remote debugging port number
The table below describes the parameters used in this browser launch template:
Parameter
Description
–user-data-dir
Specifies the path to the root directory that will store the shared browser data and user profiles
–remote-debugging-port
Opens a port for remote browser debugging over the DevTools protocol. This switch is commonly used for automated testing with frameworks like Selenium
–profile-directory
Specifies the name of the specific profile folder within the user-data-dir
–headless
Launches the browser in headless mode, that is, without a graphical user interface
The browser process runs in headless mode while utilizing the copied user profile. Consequently, all active user cookies are applied, which means sites with saved credentials will skip authentication prompts. Furthermore, the browser will log history to a new folder, keeping it completely hidden from the user’s primary account view.
Through this method, the threat actors gain access to the user’s authenticated sessions — specifically their Google account — along with the ability to erase any trace of their activity within the browser.
Code snippet showing Umbrij connecting to the browser via the debugging port
Next, the tool uses the Puppeteer Sharp library, a .NET version of Puppeteer, to connect to the remote debugging port. Puppeteer provides a high-level API to control Chrome or Chromium browsers over the DevTools protocol. Its primary use is for automated testing.
The Puppeteer module GitHub page
If the connection to the remote debugging port is successful, Umbrij sends a GET request to direct the browser to the following URL:
The value specified in the client_id field belongs to Google Workspace Migration for Microsoft Outlook (GWMMO). This is Google’s official tool for importing email, calendar events, and contacts from Microsoft Exchange accounts or local PST files into a Google Workspace account.
Umbrij also includes the ability to switch the client_id value from 279448736670 to 1095133494869 by using the -sync parameter. This second identifier belongs to another application: Google Workspace Sync for Microsoft Outlook (GWSMO), which allows users to sync email, calendars, and other data from the cloud account directly into Microsoft Outlook.
Code snippet where the client_id replacement occurs
The remaining parameters used in the request differ from those typically utilized by the legitimate applications. See the table below for a comparison of these parameters:
GET request parameter
URL used by Umbrij
Original URL
flowName=GeneralOAuthFlow
Present
Absent
code_challenge (PKCE)
Absent
Present (method=S256)
state
Absent
Present
login_hint
Absent
Present
redirect_uri
http://localhost
http://localhost:61619/callback
As seen from the list above, Umbrij omits several parameters characteristic of the legitimate applications. For instance, Umbrij drops the code_challenge parameter, normally used for data protection when retrieving an authorization code. Additionally, the tool modifies the redirection address: while the legitimate application specifies a dedicated port and a callback path, the tool simply points to localhost.
The authorization code request specifies the set of permissions for Google services required by the application. This list also differs significantly between requests issued by the legitimate application and those generated by Umbrij. The table below details the variations in the requested scopes:
After the browser navigates to the URL provided by Umbrij, the Google account selection page opens.
Account selection
Because the attackers copied the victim’s profile folder and are operating within their specific environment, the account selection options will include the currently signed-in user’s authenticated session. Umbrij identifies the corresponding element within the page’s HTML source code.
Searching for HTML code elements on the page
The tool uses JavaScript to emulate a mouse click on the elements, allowing it to proceed to the next step.
Simulating a mouse click on a page element
The subsequent step opens a page displaying the list of requested permissions.
Confirming the list of requested access permissions
As shown in the screenshot, Umbrij requests full access to email, cloud storage, and contacts. Just like in the previous step, it uses JavaScript to click the “Allow” button, which completes the authentication process.
The browser is then redirected to the local address that was specified in the redirect_uri parameter of the initial request. The tool intentionally omits a port and a path to a specific page in the redirect_uri because the true objective of this action is simply to capture the code parameter from the context of the GET request. This parameter contains the OAuth authorization code. To retrieve it, Umbrij extracts the substring located between the code= and &scope parameters.
Extracting the authorization code from the GET request
Results
Umbrij, like most other tools in ToddyCat’s arsenal, logs its actions in detail and saves them to a file. It also saves the retrieved authorization code to this log file, which the operator subsequently exfiltrates from the compromised host.
Below is an example of a log file generated by version a of the tool.
------------------------------
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[*] switch to sync mode.
[!] port 11111 is available!
[*] Impersonate <username> success!
[*] browser switch to chrome .
Parsing C:\Users\<username>\AppData\Local\Google\Chrome\User Data\Local State ...
[*] detected profile: Profile 4 ==> <email>@gmail.com
[*] ready auth for <email>@gmail.com.
[*] Browser Exe path C:\Program Files\Google\Chrome\Application\chrome.exe.
[!] CreateProcessAsUserW...
[*] Browser created with pid 3108
[???] <email>@gmail.com
[pup] mail : <email>@gmail.com
[pup] account choice click !
[pup] Allow click !
[<email>@gmail.com] 4%2F0AcvDMrDtzQaC-TT8<hash>uMhg
[*] RevertToSelf succeed!
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The log indicates that the sync mode is selected (meaning the Google Workspace Sync for Microsoft Outlook application is used) and the debugging port is set to 11111. After locating the user profile and copying its folder, Umbrij launches Google Chrome. After this, the tool emulates clicks on the appropriate buttons to confirm permissions, ultimately outputting the final result of the operation: the stolen OAuth authorization code.
Since all requests occur within a background browser instance, the tool includes a feature to generate a PDF snapshot of the web page where the permission confirmation process halted in the event of an error.
Saving a web page as a PDF file in the case of an error
Additionally, the tool can create a PDF file for the user profile in Google Chrome and Microsoft Edge by navigating to the following internal addresses:
edge://profile-internals
chrome://profile-internals
Example contents of a generated PDF file
The acquired authorization code is then exchanged for an OAuth access token. The threat actors use that token to connect to the Gmail account through the API, thus compromising corporate email communications. The diagram below illustrates the complete attack workflow.
Umbrij workflow diagram
Detection
DLL sideloading
First and foremost, defenders should monitor library loading events (DLL loads) associated with the known applications vulnerable to DLL sideloading that are exploited by this tool: Bitdefender ConnectAgent, Visual Studio, and Google Desktop Search.
title: Possible Dll Hijacking Of Microsoft VisualStudio QualityTools dll
id: 246f1409-2993-46f6-9b77-e447a327df5d
status: experimental
description: Detects possible DLL hijacking of Microsoft.VisualStudio.QualityTools.VideoRecorderEngine.dll by looking for suspicious image loads, loading this DLL from unexpected locations
author: kaspersky
date: 2025-08-11
tags:
- attack.defense-evasion
- attack.t1574.001
logsource:
product: windows
category: image_load
detection:
selection:
ImageLoaded|endswith: 'Microsoft.VisualStudio.QualityTools.VideoRecorderEngine.dll'
filter:
ImageLoaded|contains: '\IDE\Extensions\TestPlatform\Extensions\'
condition: selection
falsepositives: Legitimate activity
level: high
Browser launch
Launching a browser with a remote debugging port specified is a highly unusual event on standard user hosts that are not running web application development or automated testing workflows. Consequently, monitoring for these specific command-line arguments can serve as a reliable indicator of this attack.
title: Launching Chrome With Debug Parameters
id: f072803f-3cf4-4537-82e6-e8b3a201d99f
status: stable
description: Detects the execution of Chromium based browsers launched with incognito mode and remote debugging enabled
author: kaspersky
date: 2025-12-11
tags:
- attack.lateral_movement
- attack.defense_evasion
- attack.t1550.001
logsource:
category: process_creation
product: windows
detection:
selection:
CommandLine|contains|all:
- '--remote-debugging-port'
- '--headless'
condition: selection
falsepositives: Opening a browser as part of web application testing. Legitimate activity
level: high
Revoking third-party access
To review the authorization codes granted to applications, navigate to the Google Account settings under the Third-party apps & services section, or access the following URL directly:
https://myaccount.google.com/connections
This page displays a comprehensive list of applications and services that currently have permission to access the account.
List of apps connected to the Google account
If the Google Workspace Migration for Microsoft Outlook or Google Workspace Sync for Microsoft Outlook applications appear in this list but are not actually used within your organization, revoke their access immediately. This will invalidate all potentially compromised OAuth tokens associated with them.
Risk mitigation
Launching a browser with a remote debugging port enabled is inherently suspicious for users who do not engage in web development. For these employees, you can completely disable Chromium-based browser developer tools.
This can be achieved by configuring the DeveloperToolsAvailability policy. To enforce this, set the registry value to 0x00000002 for the following Windows Registry key and restart the browser:
To verify that the policy has been successfully applied, navigate to the browser’s internal policies page at chrome://policy:
Note that while disabling developer tools can successfully disrupt the automated retrieval of the OAuth authorization code, it will not help, however, if the adversary decides to leverage the browser’s graphical user interface (GUI) — though this manual approach is significantly less likely due to the friction it introduces for the attackers. Therefore, as a risk mitigation measure, users should be instructed to explicitly log out of their Google accounts as soon as their sessions are complete.
Takeaways
The ToddyCat APT group continues to search for ways of compromising corporate email communications. We have been tracking the group for a long time and we have observed continuous updates to its arsenal in an attempt to bypass security defenses, even as their core techniques remain consistent. For instance, the group has long relied on DLL sideloading to stealthily drop malicious utilities and scheduled tasks. However, their new tool, Umbrij, automates the attackers’ attempts to gain access to organizational email accounts. This automation not only helps increase the scale and frequency of their attacks but also demonstrates ToddyCat’s strong motivation and advanced technical skills.
To defend against these threats, corporate security teams must monitor for suspicious library loading events initiated by legitimate files, watch for instances of browsers launching in developer mode, and conduct regular audits of third-party applications and services with access permissions to Google accounts. Furthermore, deploying a robust, comprehensive security solution — such as Kaspersky Next — is critical to detect this type of malicious host-based activity in a timely manner.
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