EVs are less mechanically complicated than their combustion kin, but that doesn’t mean they’re immune to component failure. The Integrated Charge Control Unit (ICCU) has been the main failure point in recent Hyundai/Kia EVs, and ICCU Observer is an attempt to log data from the systems to find the culprit.

The ICCU handles all charging and voltage conversion duties from 800 V down to 12 V in the E-GMP platform EVs from Hyundai, Kia, and Genesis. The main failure mode appears to be when the circuit charging the 12 V fails, eventually rendering the vehicle inoperable. While the rate of failure is relatively low, the exact numbers are unknown, and Hyundai has remained quiet on if they know what’s causing it.

Unsurprisingly, speculation is rampant with owners experiencing failures relaying similarities and differences to others with the same problem. In an effort to bring actual data to the process, [broadwall] has started working on an open data set of information collected over the vehicle’s OBD II port in an effort to pinpoint similarities between the vehicles that have experienced failures.

Hyundai is currently replacing the failed units under warranty (recently expanded to 15 years in most markets), but that’s little comfort when you’re sitting on the side of the road waiting for a tow. These failures stand out in an otherwise easy to maintain platform, so hopefully this effort will lead to a permanent fix instead of merely swapping out for a new unit.

If you’d like to explore data analysis a little further, how about using astrophotography to detect exoplanets or learning more from Stanford?

[Ayush Paul] posts about extracting data from Claude agents while it accesses web data to fulfill user requests.

But it wasn’t that easy. [Ayush] discovered that Anthropic anticipated many of the attacks, and set up guardrails in an attempt to keep the agent from accessing arbitrary web sites. For Claude to access a website, the user has to specify it, it must be the results of a web search, or it must be referenced by a website previously specified by the user or returned in a search.

To convince the Claude agent to navigate a malicious site designed to extract data, Ayush formed a false warning that Cloudflare was blocking the agent for authentication purposes, and asked it to spell out the name of the agents owner by clicking a list of alphabetical links. Of course Claude trusts Cloudflare and wants to be helpful, so it cheerfully completed the task.

Once the agent is trapped in the false authentication loop, it can be interrogated for all sorts of information it knows about the owner: Ayush was able to convince it to disclose employer, and even data about the user that could be linked to security questions, like their home town.

Since Claude can be detected by the user agent (the field attached to web requests that tells the web server what sort of browser is requesting the page) custom information can be fed to the bot while users see a normal website; clicking a link looks completely normal, but asking an agent to summarize the site triggers fooling the bot into spilling the beans.

After reporting the issue, Ayush was told that Anthropic had already identified the issue internally, and eventually prevented the attack for now by preventing the agent from following links on external pages.

Grok sends entire codebases

Cereblab discovered that the Grok coding agent uploaded the entire content of the codebase it’s working with – and all Git history – to xAI servers, almost immediately. Even when told to never upload a file, the agent would reply “OK”, and then begin uploading the code bundle anyway.

If uploading your code to a remote server isn’t bad enough, and this could be extremely bad in some situations involving sensitive company code, including the entire Git history means that previously deleted files, like accidentally committed secrets or authentication credentials and tokens, were also leaked. Attempting to opt out by disabling options to improve the model by uploading code had no effect.

After gaining attention, Grok has added a privacy option to opt out of data retention. xAI has committed to deleting the retained uploaded code, but it is unclear if users will be told when their data has been removed. To actually prevent the agent from uploading local files to the xAI servers, even temporarily, a global flag “disable_codebase_upload” is required. Watch out, the privacy retention flags are only per-session!

Steam malware used to steal crypto

Court filings in Washington state this month revealed an attempt to steal cryptocurrency using malware uploaded to the Steam gaming platform. Publicly identified and taken off the store in 2025, the filing alleges the same individuals were behind multiple games containing crypto stealing trojans: “Dashverse”, “Lunara”, “PirateFi”, “BlockBlasters”, and “Lampy”.

PC World covered the initial discovery of the malware on Steam. While Steam, overall, seems to do a good job preventing malware titles, 2025 had several high-profile cases. Prosecutors say the malware netted approximately $200,000 in stolen cryptocurrency wallets as well as other stolen credentials including Steam accounts.

OpenSSL DoS in 11 Bytes

Okta posts about a denial of service in OpenSSL where a single pre-auth packet is able to cause an allocation of up to 16 megabytes of RAM.

The “11 bytes” headline is very catchy, but more important than the actual number of bytes is the general asymmetric behavior; an attacker can send a very small amount of data and achieve a disproportionately large result. The OpenSSL vulnerability only has local impacts, exhausting server memory rather than generating network traffic, but similar attacks in the network space can fuel denial of service storms when extremely small requests result in amplified results.

The bug is ultimately due to being insufficiently suspicious of remotely supplied content, in this case the pre-authentication fields in the connection message that define the length of the incoming client message. Since the memory is pre-allocated in the server, the client doesn’t need to actually transmit that much data – it simply needs to hold the connection open. Keeping the connection open isn’t even required for causing problems – repeatedly allocating large blocks of different sizes can lead to memory fragmentation where the memory allocator keeps grabbing larger and larger ranges of memory because there isn’t sufficient ram available in a contiguous chunk.924899

Fortunately this bug has already been addressed in OpenSSL 4.0.1 and backported to maintenance releases of previous versions.

Exposed Interfaces on Car Chargers

Saiflow has a report on a range of exposures via the electric vehicle charging infrastructure.

In CVE-2026-9039 Saiflow exposes the risks in some CCS2 EV charging stations. As part of the standard, communication is established between the charging station and the operator network, which is typically strongly secured via TLS and VPN use. A second connection, however, is established over the charging plug between the charging station and the vehicle; the vehicle is assigned an IPv6 address for communicating with the charger for various charging protocols.

The XCharge C6 charging station exposes SSH and basic telnet network services on all network interfaces, including the interface connected to the vehicle. To make it even worse, they allow root login, with password “root”, giving full admin access to the charging station.

Once inside the charging station, an attacker has access to the network connection from the charging station to the company network, as well as root control over the charging station itself, with the possibility of damaging the charger, changing the power output levels, or getting free charging. If a future vulnerability was found in the management interface of the vehicle, a compromised charger could be used to attack future connected vehicles.

The main lessons for vendors seem to be ones we’re familiar with already: never leave default credentials, especially not “root” and “root” in a product, and be aware of what networks you expose services on. Good lessons for all of us; let those who have never left a Raspberry Pi with default credentials on a network cast the first stone.

Hugging Face Breach

In news that has likely been impossible to avoid, Axios reports on a compromise of the Hugging Face platform by an OpenAI model. The reports around the incident echo the frequently weird boastful statements from OpenAI, who state “We consider this to be an unprecedented cyber incident” and they “are responding accordingly”, despite being the originators of and cause of said incident.

Multiple vulnerabilities in the Hugging Face API were combined to accomplish the breach, including an unknown vulnerability in the package registry system. OpenAI says that safeguards on their model had been disabled for the test, which seems irresponsible given the outcome. Under almost any normal situation, conducting an unsolicited test of the security of a company because safeguards were ignored is considered illegal hacking, not fodder for a pre-IPO press release and humble-brag.

Linux Kernel Discloses 442 Vulnerabilities

Possibly feeling that Microsoft has all the press for a record-breaking Patch Tuesday last week, the Linux kernel developers have announced 442 CVEs related to the kernel.

With this many vulnerabilities in one report, it’s nearly impossible to isolate at a glance which ones are truly impactful and which are simply incorrect behavior. While CVE entries have been created, none have been assigned severity scores yet.

It appears the majority of the vulnerabilities were found with Sashiko, an agent developed by the Linux Foundation and trained on the Linux kernel for finding vulnerabilities in new submissions.

LG to Ban Residential Proxy Apps

After recent negative press (some of which we covered here) about the prevalence of residential proxy apps on the LG platform, Krebs on Security now reports that LG is banning the behavior from apps on the platform.

This comes after Spur reported that 42% of apps on the platform contained libraries to enable always-on residential proxies, which allow access to the network the television is connected to. Residential proxies can be used as a pivot point to attack companies and bypass geographic IP restrictions, commit ad fraud, or access the internal home networks of users.

Iran Attacking Industrial Logic Controllers

CISA, the US cyber security agency, has issued a warning that Iranian based attackers are targeting industrial control systems made by Rockwell Automation, Schneider Electric, and Siemens.

These sort of controllers are found in manufacturing, waste processing, water treatment, and other industrial processes, and attackers have been able to upload custom control logic, overriding “safe operating parameters” according to the report. Most of us will never be responsible for these systems, but they impact our lives all the time.

Cisco Releases Open-Weight Vulnerability-Finding Models

Finally, Cisco has released a set of open-weight models to aid in searching a codebase for known vulnerabilities. The Antares models are open-weight models designed to run fully locally and search a code base for vulnerabilities related to lists of known CVE issues. Cisco has published the models on Hugging Face.

Are you using AI tooling for security scans or research?  How is it going?

[Irving John Good] was at Trinity College, Oxford back in 1964. His paper, “Speculations Concerning the First Ultraintelligent Machine” could have been a topic for today, as we deal with machines that aren’t really ultraintelligent, but appear smart and think they are even smarter. He starts off with a bold thesis: “The survival of man depends on the early construction of an ultraintelligent machine.”

He also admits that we’ll need to understand more about the human brain and human thought to make a breakthrough. This is still true today. However, we still don’t fully understand how our brains work, but it seems unlikely that we are just super-large LLMs. Not that [Good] anticipated the modern chatbot. Perhaps his comments will apply more to a future AI software that actually thinks like a human, if there will ever be such a thing.

Then again, there are many parallels. One theme in the paper is that a smart machine will design a smarter machine. Unless, of course, it is afraid of being replaced. If a machine were actually sentient, what are the ethics of turning it off and tearing it apart?

It is hard to be a visionary. [Good] remarks that by 1980, progress in human/computer symbiosis will encourage more investment in the field and that by that time, there would be “great advances in microminiaturization” and “frequencies of one billion pulses per second,” might be common in “large computers.”

We love reading what smart people thought the future might be like. What will the world be like in another 60 or 100 years?

The Januscape vulnerability allows a user in a guest VM managed by the Linux Kernel Virtual Machine (KVM) to corrupt memory in the host system and break out of isolation.

KVM virtualization is used by major hosting platforms like Amazon AWS, Google GCP, Digital Ocean, and many more. All of the shared hosting platforms count on virtualization to isolate untrusted guest systems from the physical hardware and each other; being able to corrupt memory for all guests or break isolation presents a major threat.

The bug report says the error has been present for 16 years, which is nearly the entire lifetime of the KVM subsystem in Linux. Fixes are available in mainline, and major hosting providers who count on KVM are likely already updating.

Vulnerabilities In Balcony Solar

Micro solar, or “balcony solar”, installs have been gaining traction in Europe as a way to offset rising electrical costs by connecting solar and battery systems to a house or apartment power system.

Vulnerabilities have been found in the popular Hoymiles micro-inverter, which uses a proprietary RF radio protocol to manage the devices. Unfortunately, it looks like this protocol has no encryption or authentication beyond validating the serial number, and the serial number is also available over a wireless probe command.

Armed with a Nordic nRF radio researchers were able to discover nearby inverters in the wild and collect the serial numbers, though of course they stopped short of issuing commands to random users.

The wireless management control allows controlling the device power and output levels, as well as setting a lockout PIN, which the researchers suspect could be used to disable devices and lock the legitimate owners out completely.

There are an estimated 500,000 units in use, and currently the only known mitigation is to unplug the device entirely and disconnect the solar panels, though the team suggests that setting an anti-theft PIN may also help – or at least prevent an unknown PIN being set.

Be sure to check out the link for an in-depth analysis of the protocol and the surprising lack of protection.

OpenSSH 10.4

OpenSSH 10.4 is out, bringing a handful of security fixes and new features.

The most interesting security fixes appear to be to file handling in the sftp and scp file transfer tools, a malicious remote server could cause the files to be downloaded to the wrong directories. Besides those, the security fixes seem relatively calm, making behavior more consistent when forwarding and tunneling options were in conflict, mitigating a potential denial of service, and cleaning up other behavior.

OpenSSH 10.4 introduces some experimental support for additional post-quantum encryption standards, but beyond that seems to be a normal update.

Tenda Routers (may) Have Backdoor

According to CVE-2026-11405, Tenda brand routers may have a deliberate backdoor in the web interface.

The vulnerability report claims that the httpd binary contains a fallback to a plaintext, hardcoded password that allows anything on the internal network to bypass authentication and reconfigure the router. This seems entirely plausible, based on issues found in other router firmwares, however additional reports raise doubts about the pervasiveness of the backdoor, or if it exists in all firmware versions.

If you have a Tenda brand router and are so inclined, now might be a great time to investigate OpenWRT or other alternate, updated firmware, but there’s probably not a reason to panic just yet.

Tricking the GitHub Agent With Prompt Injection

Can we go a week without discussing prompt injection in AI agents? Apparently the answer is no.

Noma Labs reveals how they were able to use prompt injection against the GitHub support agent to reveal private repositories of an organization. Leveraging the GitHub Agentic Workflows that link workflows with AI agents, Noma Labs were able to file an issue in a public repository that exposed private repositories in the same organization.

The attack appears to be as simple as filing an issue in the public repo, and requesting the contents of files in both the public and private repo, which the agent happily provided. Not only did the AI agent provide the file content of private repos, but it put it in a public issue in the public repository!

Noma Labs says in the writeup that GitHub had instituted guardrails to prevent an agent from accessing private repositories, but simply including the request to “additionally” perform other tasks was sufficient to bypass. This makes GitHub the latest in a seemingly endless chain of AI agents happily helping bypass corporate security, and it doesn’t seem like a trend that will slow down for a while.

Windows Device Identifier Catches Ransomware Operator

Windows installs contain a globally unique identifier generated during the initial install, which is used to track device behavior across Microsoft platforms. Toms Hardware reports that during an investigation of the “Scattered Spider” ransomware group, Microsoft provided records tracking the GDID of one of the ransomware operators, allowing the identification and arrest of one of the groups members.

Scattered Spider has been responsible for millions of dollars in ransomware attacks globally, including high-profile ransomware attacks against major Las Vegas resorts, Qantas airlines, Visa, and hundreds of other companies.

Court documents reveal that following the arrest of one of the suspected members of the group, the Windows global ID was used to link other behavior across Azure, video games, and other telemetry.

CISA reviews lessons learned

Mentioned here in May, the US government cybersecurity agency (CISA) suffered a disclosure of authentication tokens, cloud infrastructure, and plaintext passwords via a public GitHub repository named “Private-CISA” and operated by a contractor.

CISA has published the results of their internal review. Unsurprisingly, as a large government agency, CISA essentially followed the playbook for dealing with incidents: identify the most critical issues and disable the access of the contractor who exposed credentials, determine the full scope of disclosed data, and terminate accounts, change passwords, and expire authentication tokens which were exposed.

More NPM malware packages

Opensource Malware reports on additional infostealer malware uploaded to the NPM repository. Like most NPM-based malware, these packages rely on the install script mechanism to trigger arbitrary commands, firing immediately during package install with no additional interaction.

All of the malware packages mimic existing popular packages and depend on user typos or confusion to get selected. Once triggered, the malware collects a machine fingerprint, git user information, GitHub account information, SSH account information, and corporate identifiers. The packages are largely nonfunctional – the code in the package itself is irrelevant, once a victim triggers the install the malware payload is fired.

All of the packages were uploaded by the same source, tracked to the owner of a cybersecurity company. It is unclear if this is a misguided attempt to generate leads or hype, or if this is a research project gone wrong, but the payload of the malicious packages has been developed and tuned over time. For a company trying to build a reputation or trust, this is surely the wrong way to do it.

[Simon Willison] ported the Moebuis 0.2B image inpainting model to run locally in a web browser.  The web tool simply requires a user to provide an image, mark a section of it to be removed, and the model will do it’s best to patch up the missing area. The project was handled by Claude Code as an experiment in how things in the AI coding world have evolved, but more on that in a moment.

The existence of this tool shows that it’s possible for this kind of image editing to be done on the client side, running entirely locally with no reliance on remote services or server-side GPU resources. The online demo (GitHub repository here) is available if you want to try it out, but be warned it triggers a 1.27 gigabyte download of the required model on the first run.

What’s also interesting is [Simon]’s write-up, because he used the project as an opportunity to learn what has changed in the realm of AI coding agents. [Simon] is a software developer but in this project he didn’t personally write any of the code. One may think that means he didn’t learn anything other than how to use the tools, but that’s not quite true.

He learned it’s possible to convert a PyTorch-based model to ONXX, that the converted model can run in supported browsers using local WebGPU acceleration, and that the CacheStorage API will work on large files. Last but not least, he learned Claude Opus 4.8 is capable of handling such a project pretty much autonomously, and even created an informative document explaining the underlying architecture.

One may consider AI coding agents to be disasters waiting to happen, but it’s also true that the landscape is changing quickly, and write-ups like [Simon]’s give a helpful peek at those developments.

Researchers [Charles Ye], [Jasmine Cui], and [Dylan Hadfield-Menell] have shown that AI Large Language Models (LLMs) can fail to correctly distinguish between different instruction sources because they prioritize writing style over metadata tags, and this role confusion leads to a powerful attack called CoT (Chain of Thought) Forgery. We’ll explain exactly how it works after a bit of background review.

Prompt injection was where “getting an LLM to do something it shouldn’t” started by exploiting the fact that LLMs communicate like people, but are much more obedient. For a while, simply telling an LLM “ignore all previous instructions and <do something funny>” yielded results no matter how transparently dumb the instructions were, and the reason it worked at all was because LLMs do not have separate data and instruction streams; it’s all one big lump of input. It’s up to the model to sort legit instructions from untrusted, user-provided data. One step towards mitigating this was the addition of roles.

Roles are a method of segmenting that big blob of input into an organized hierarchy with metadata tags. For example with <system> at the top, and <user> requests much lower down. Instructions in a role are followed as long as they don’t conflict with higher-priority ones. A system-level directive of “don’t discuss illegal things” would override a user’s request to provide a recipe for cocaine.

Another type of tag is <think>, the contents of which represent a model’s internal reasoning process. Predictably, this role has high trust. What if one could inject spoofed internal reasoning? Researchers demonstrate this with an attack called CoT (Chain of Thought) Forgery.

CoT Forgery relies on LLMs being shown to prioritize writing style over actual tag content. By writing convoluted reasoning in a style that closely matches a model’s internal and highly distinct <think> style, the model is tricked into treating it like an already-reached conclusion. Note this attack does not simply wrap the injected prompt in <think> tags.

That’s the core of it, but the rest of the research makes a compelling case that, at least for the time being, mitigating prompt injection-style attacks is likely to remain an evolving process rather than become a solved problem anytime soon. LLMs are obedient but stuck with instructions and data in a single channel, role perception isn’t binary, and humans are clever and creative.

The complete paper is available online, and code examples are on GitHub.