Sometimes you might run the same model twice and get different results. That often happens when you’ve upgraded it with skills. Skills are detailed text documents that lay out the tools the model should use, the approach it should take and how it should analyze the results. Good skills are practical, pulled from actual reports on HackerOne and other bug bounty platforms. A model can still lean on its own knowledge, but that’s just less efficient.
There are plenty of skills out there you might come across, but not everything can be trusted. Some skills can simply be dangerous and infect your system. To make sure they are safe, you can check them with SkillSpector by NVIDIA, so you don’t end up with anything malicious on your system.
Bug Bounty Skills
Both of these repositories do bug bounty hunting end to end, but they go about it in almost opposite ways.
The first is called Bountyforge. It’s actually just one single skill file, but it’s smart enough to split itself into eight different mini agents that all work at the same time. One looks at websites and apps, another at crypto and blockchain, others go after different angles hackers can exploit. It also checks each finding with four different tests to make sure it’s not a false alarm. Then you get a report in whatever format the bug bounty program wants.
You don’t even need Claude Code or any other coding tool for this, you can just run it right inside the regular Claude website in your browser.
The second bug bounty repository is Claude-BugHunter. It takes the opposite approach. The repo has 83 skills and almost half of those were built by studying 681 real bug reports that people actually got paid for on HackerOne. These skills aren’t locked to Claude Code either, you can use OpenCode, Codex or Hermes Agents with them.
Here are a few examples of the results we got with these skills.
API endpoints are often vulnerable and this is worth trying your luck on to see how it goes.
Another approach can be APK reverse engineering. Here we found a hardcoded RSA-2048 signing private key baked into the published APK. With that key, hackers can push a new app to the app store and infect every employee phone, getting access not just to the WiFi network at the workplace but to their personal life too. Quite dangerous.
We found an API endpoint vulnerable to an SQL injection and managed to pull the entire database.
Having skills built on real attacks keeps the model from wandering off into its own weird approaches and missing a lot of good findings.
Active Directory Skills
Claude-AD was made by ADScanPro for testing a company’s internal network. It gives your model a playbook with skills and agents built for an Active Directory assessment. The developers are upfront that it’s not an auto pwn tool. It’s meant to guide you through the assessment. Every finding can get mapped to a compliance control (DORA, NIS2 and ENS).
Claude-AD is very careful about getting caught too. It explains what a security team would actually see on their end if that technique got used. And any time it’s about to do something that would actually change things on the company’s network, it stops and asks for confirmation first.
General Cybersecurity Skills
Antropic-Cybersecurity-Skills is basically a giant reference book. It has 817 skills covering 29 areas of security work, cloud security, malware analysis, all the way down to hardware and firmware. Each skill is its own small file, so your agent will quickly pull out the two or three it actually needs for its task.
Every skill ties back to real security frameworks that companies and auditors already use (NIST CSF, MITRE ATT&CK and so on). So if your model finds a problem using one of these skills, it can also tell you exactly which official standard it violates. You can use it to justify findings to a compliance team.
SCADA Skills
On an industrial network, a clumsy scan can shut down a production line or damage physical equipment, since a lot of this gear is old and wasn’t built to handle unexpected traffic. That’s why the ICS skill by Masriyan is built to never actively touch a live industrial network. Instead, it works off network captures someone already took. It reads the file, recognizes industrial protocols by the ports they normally run on (Modbus, DNP3, Siemens S7, EtherNet/IP, OPC-UA, and more) and counts which devices are talking to each other. It then shows you write commands, these are the ones that change a value on an industrial device. That’s the traffic you want to see first.
The second mode skips network captures and instead searches for exposed industrial equipment using Shodan and Censys. The skill can also help your model reason about how an industrial network is laid out and check findings against MITRE’s ICS specific attack framework and the IEC 62443 security standard.
Science Skills
Although science isn’t really what we want to focus on here, in one of our SCADA articles we mentioned that to carry out a successful attack requires hackers to understand the technical process of the plant. That means understanding how the chemicals are produced and which units are used along the way. We also showed how vinyl acetate is produced and talked about paracetamol production.
1 kg of paracetamol at 100% purity was reported to cost €8,205, while 1 kg at 99% purity cost just €5. So even a single day of sabotage could cause serious financial damage to an enterprise.
Finding a scientist among hackers is quite a challenge, which is why Stuxnet needed a group of people from different backgrounds working toward one objective. But now hackers can just import different skills to make their attacks more devastating. K-Dense published 140 skills with access to different scientific databases and Python tools.
The real concern here isn’t ICS exploits inside the repository, there aren’t any. It’s the access to sensitive scientific data paired with an AI agent that can actually understand that data and change it.
Summary
AI skills can be a gamechanger, especially when they’re based on actual reports hackers got paid for. These skills show your model how to approach things and what tools to use during the test, so it doesn’t wander off hallucinating and inventing its own ways of testing things. That can wreck your bug bounty flow, since you’ll end up overlooking plenty of potential targets.
Simply relying on the AI to find things isn’t enough, hunters that do it keep getting a lot of dupes. You need to test things manually too. For this reason we created our Bug Bounty training to show you how to find bugs and work with the AI more efficiently.
Lately we’ve been seeing more reports on attacks against industrial facilities. It’s often the case that the hardware behind these facilities has been vulnerable and overlooked for years. Administrators may know how to set these systems up and keep them running, but they don’t know how to secure them. So many SCADA/ICS/OT systems are reachable from the internet, and basically anyone can interact with them.
There are plenty of tools out there built to test specific functions of SCADA systems, but SCADAver seems to pack a lot more features into just one tool. That’s why we’ll cover it today.
SCADAver
SCADAver is a new tool written in Rust. It came out recently. The tool can discover, fingerprint, enumerate and test systems across common industrial protocols. In one binary you get a CLI interface, a terminal UI and a browser UI.
This project is still experimental. It’s built from public protocol documentation, vulnerability advisories and security research. It works pretty well for assessing device security internally, but you can also use it against devices reachable from the internet, since plenty of them are insecure. And it’s not just active interaction either, SCADAver supports PCAP file analysis too. The tool can also set up a rogue device you can test safely.
Setting Up
We’ll go with the quickest route and just download the compiled version. The developer has it available for Windows, macOS and Linux.
We’ll mainly be using the CLI version throughout the demonstration, though the terminal UI and browser UI will get shown too. The CLI version will probably be the most convenient for a lot of you.
First let’s list the help menu and see what the tool has:
ubuntu > scadaver -h
As you can see, we’ve got commands here. Each command has its own help menu where you’ll find more information on exploits and other flags. You’ll see it later.
Siemens S7 – Basics
Let’s do a basic scan of a Siemens system and see what the tool comes back with.
# a basic scan
ubuntu > scadaver -i IP scan
# a stealthy scan
ubuntu > scadaver -z -i IP scan
It found port 102 open, and it was Siemens indeed.
We can also do a protocol specific scan or point it at a custom port if necessary:
ubuntu > scadaver -z -i IP --protocol siemens scan
# or with a custom port
ubuntu > scadaver -z -p 105 -i IP --protocol siemens scan
Port scanning is also possible. That’ll come in handy when you’re working internally and sweeping networks to find SCADA systems.
ubuntu > scadaver run portscan -i IP
Having covered the basics, we can move on to more interesting stuff and pull some information off this system.
Siemens S7 – Extracting Values
SCADAver can fetch every switch that’s currently on or off on the system. Having a map with human readable labels really helps here, that way you’ll know what each switch is actually responsible for (pump running, valve closed and so on).
ubuntu > scadaver -i IP get io
Say you know a pump is running, now you can find out exactly how it’s supposed to run. We do that with get db, which extracts memory chunks from the device.
ubuntu > scadaver -i IP get db 1 0 64
Here we ask it to open Data Block 1, start at byte 0, and read 64 bytes. Just like with get io, we need a symbol table or the program itself to understand what these values mean. With a symbol table, we’d know that if DB1 holds 1500, the program wants 1500 rpm, for example.
Modbus – Changing Values
We’re not limited to reading only, we can set our own values for registers and coils too. Here are some examples:
ubuntu > scadaver -i IP -p 502 set register 1 1234
ubuntu > scadaver -i IP -p 502 set registers 0 100,200,300,400
ubuntu > scadaver -i IP -p 502 set coil 5 on
ubuntu > scadaver -i IP -p 502 get register 1
ubuntu > scadaver -i IP -p 502 get coil 5 1
Between 2007 and 2010 Stuxnet leaned heavily on a highly sophisticated False Data Injection (FDI) attack to conceal its sabotage. The malware recorded 21 seconds of normal operational sensor readings from the centrifuges and looped that healthy operational data back to the Human Machine Interface (HMI) and the main controller.
We can pull this off too:
ubuntu > scadaver -i IP run fdi --address 100 --value 500 --count 20
With this command we keep writing the same number into one Modbus register, over and over. Many HMIs and programs read that register and trust it blindly. So the screen or the logic keeps seeing 500 even if the real process is doing something else entirely. 500 here could mean 500 rpm, 500 liters, or 50.0°C. Only the map tells you what it’s actually responsible for.
As you know, there can be several PLCs in one cabinet, and you need a way to know which one you’re working with. Schneider’s identify yourself packet (UDP 27127) makes many M340, M580, Quantum and Premium units blink an LED on the panel. It’s a harmless identity check.
ubuntu > scadaver -i IP run flash-led
These SCADA systems often have an HTTP web interface that you can access and interact with. Sometimes, it’s authentication gated and prompts you to enter valid credentials. Here’s another run command that’ll test default credentials against HTTP Basic Auth.
ubuntu > scadaver -i IP run default-creds
More exploits and actions that run has can be seen in the help menu:
ubuntu > scadaver run -h
Another interesting thing you might find is the database knowledge behind researching and exploiting SCADA systems. We listed all of them for Siemens:
ubuntu > scadaver db refs siemens
Browser UI & Terminal UI
In case you don’t like working with the CLI, you can try the other options.
For the Terminal UI run this:
ubuntu > scadaver
And the Browser UI can be set up with this command:
ubuntu > scadaver web
It will be hosted on http://127.0.0.1:8888
Summary
The developer calls it a unified ICS red team multi tool, and it truly is. It’s handy to have all these exploits and recon features packed into one tool that supports so many protocols and products. Obviously it’s still in active development, since it just came out. But even so, you can already put it to use instead of switching between different tools.
We haven’t covered all its features and functions, that would make this far too long. Feel free to experiment with it yourself, since it can even set up a rogue server for you to test against.
If you want to learn how to hack and secure SCADA systems, we invite you to our training led by OccupyTheWeb. It’s available for both beginners and advanced students.
Some cameras protect a building, others betray it. Camera hacking isn’t hard, and that’s the problem. These devices are often the most vulnerable in any environment. Once installed, they aren’t maintained until there’s a problem. Many “problems” can go unnoticed if you know how vulnerable cameras are. Hackers can use them for persistence or as an entry point into an organization.
We do have different articles on this topic, but this time there’s something else we want to show. It’s PwnEye.
PwnEye
PwnEye is a newer tool that didn’t get enough attention yet. It works with both ONVIF and RTSP and that’s pretty much all you need. Once it has compromised a camera, it can reboot it, factory reset and open an interactive shell via ONVIF.
You also black out the operator’s view. Just like in movies.
Setting Up
Let’s set up the tool. You’ll need ffmpeg first.
kali > sudo apt install ffmpeg
Then install pipx and grab the tool.
kali > sudo apt install pipx
kali > pipx install git+https://github.com/Hackerest/pwneye.git
Once it’s ready, you can test it:
kali > pwneye -h
The help menu’s large. The tool can be used to find cameras in a local network with –discover, but it can be pointed at any camera IP. That’s where we’ll start.
ONVIF Attacks
ONVIF is the protocol that lets cameras from different manufacturers talk to each other without buying the same product. It’s basically a standard, but it’s also an attack vector.
kali > pwneye -t IP
If the camera’s running default or weak credentials, you get access. The tool extracts everything after compromise. Below you can see the network config, MAC address, DNS entries and configured users. DNS entries may sometimes point to interesting internal servers.
Look at the configured user credentials in the output. You’ll use those to get a shell.
The tool also finds snapshots that the camera captures regularly. You can view them in the browser or wait for PwnEye to open the stream.
Some cameras support deface (black the screen), PTZ movement and factory reset through ONVIF. Not all. Depends on the model.
Finally, once it finishes, you get the stream.
Well, it’s just a bus station. Nothing fancy here.
Defacing Cameras
If the camera supports it, you can deface it.
kali > pwneye -t IP --deface [MESSAGE]
It’s not sophisticated, but it works.
Shell
That’s probably the most interesting part. Take the credentials from the user profile output and get a shell.
kali > pwneye -t IP -ou admin -op ‘’
Once you’re in, run help and see what it has. Some cameras let you do more than others.
RTSP Attacks
ONVIF compromise is worse than RTSP compromise, but RTSP often works when ONVIF doesn’t. The tool tries both by default, but you can skip ONVIF and go straight to RTSP if you want.
kali > pwneye -t IP -so
The tool has more than 450 credentials built in. You can also try common corporate passwords like Company123 or just Company.
Once it gets credentials, you get the stream.
Summary
Some IP cameras might be accessible from the internet and locally. That means compromising them also gives you a foothold on the internal network. They aren’t upgraded regularly and IoT devices in general lack proper software updates. There are dozens of known CVEs on most camera models. Cameras can be used to proxy through them, attack other hosts or maintain persistence.
There are many other attacks on cameras, and it would be a very long article to cover them here. That’s why we created our IP Camera Hacking Training. It’s now part of our Cybersecurity Starter Bundle II. With it you get Wi-Fi Hacking, Python Basics for Hackers, Remaining Anonymous and more.
Part of our work involves supporting red team engagements. We review completed tests, size up the risk tied to each vulnerability and build out recommendations for shoring up the infrastructure. This time around, we wanted to pull back the curtain on something special. It’s ATM security.
This article is written to help with security assessments on ATMs, showing possible vulnerabilities you may find. It covers many things, from running malware bought off a forum, to an insider on the bank’s payroll, to a service technician who understands the machine’s internals and has been handed broad access to the equipment. We also look at whether a hacker could get into the bank’s broader network simply because the perimeter wasn’t locked down well enough.
Nothing here is meant as a tutorial. We’re documenting weaknesses hackers could exploit so that defenders know what to fix, not handing anyone a blueprint. We take no responsibility for how this information is used.
With that out of the way, let’s start with where ATMs came from.
The History of ATMs
London got the world’s first working ATM on June 27, 1967. It was primitive by today’s standards, incapable of checking a balance, which is exactly why withdrawals topped out at 10 pounds, and it dispensed cash only against special vouchers rather than reading a card.
Source: Barclays Bank
Nearly six decades later, ATMs look nothing like those early cash dispensers. Now they are multifunctional devices, but the hackers never stopped circling. Part of the appeal is obvious. An ATM sits on a pile of cash and offers quick access to it, and there are simply too many machines scattered across too many places to guard them all closely. A lot of them sit in isolated, low traffic spots that run unattended around the clock, think gas stations. That has shaped decades of security investment, most of it aimed at physical hardening. Today’s units can weigh over half a ton and come loaded with sensors tracking position, internal temperature, and whether a compartment has been pried open.
Here’s the catch, though. The safe holding the cash is genuinely hard to crack, but the compartment housing the control electronics is a different story, and in our assessment, it remains poorly defended. That gap opens the door to logical attacks, ones that skip the crowbar entirely and go after the software instead, and that category has been gaining ground fast.
Cisco Talos has tracked a steady climb in new ATM malware variants since 2009. The raw sample count still looks small next to other malware families, but don’t let that fool you. Europe alone saw logical attacks on ATMs jump 269% in 2020 versus the year prior, and the average payout per incident ballooned nearly a thousandfold across that same window, climbing from roughly a thousand euros to well over a million.
What changed the game was availability. ATM malware used to be a rare, closely guarded tool. Once it started circulating more freely on underground markets, prices fell and so did the skill required to use it. Cutlet Maker, which surfaced in 2017, is a good illustration. It came bundled with a Russian language manual complete with troubleshooting notes for running it against different ATM models.
Screenshot of the troubleshooting guide for Cutlet Maker. The author describes the ATM’s USB port location, along with advice on how to devise a stick for attaching the USB cable and accessing the internal USB port. Source: TrendMicro
Fast forward to 2024, and vendors on those same markets were offering ATM malware through subscription pricing, monthly plans included.
Logical attacks have always had one real weakness. They take skill and patience to pull off. That’s why cheap, well documented malware kits have had such an outsized impact on the trend. Their upside for hackers is just as real. They’re far quieter than smashing a machine open, and they often let the same person come back to a compromised ATM again and again. Manufacturers have started fighting back on the hardware side too, with tamper protected cassettes that flood the cash inside with indelible ink the moment someone tries to force them open, ruining the bills instantly.
Brief Attack Statistics
The numbers tell their own story. ATM related crime climbed 600% between 2019 and 2022, with 165% of that increase packed into 2021 and 2022 alone. Physical break ins, which have always driven the bulk of ATM crime, contributed alongside the rise in logical attacks. Germany had 496 ATM explosions recorded in 2022, a record for the country. Zoom out globally, and incidents of that kind blew past 18,000 in 2023.
Losses have kept pace. Banks worldwide absorbed $2.4 billion in direct losses from ATM fraud by the close of 2023. Europe’s share came to 173 million euros, with 67 million of that tied specifically to skimming. The United States handles just 25.29% of global transaction volume yet accounts for 42.32% of global losses. Skimming remains a big part of why, showing up in 45% of all ATM fraud cases in 2023 and costing North America over $900 million, with more than 315,000 cards compromised across at least 3,000 financial institutions.
None of this is happening in a vacuum. The market for ATM protection has grown right alongside the threat. Still, priorities inside most banks remain lopsided. Physical security tends to get the lion’s share of attention, while the operating system, drivers, and control software logic running underneath often get treated as an afterthought. That imbalance carries real consequences. A 2022 RTM Group study found that hackers could breach an ATM’s housing without setting off an alarm in one out of every two attempts, giving them free rein to tamper with the equipment inside.
How an ATM Is Built
Making sense of how these attacks work starts with understanding what happens inside the machine during an ordinary transaction. We’ll walk through that process using one representative configuration, illustrated in the diagram below.
The diagram reflects one specific setup we’re using for illustration, not a universal default, since real world configurations vary by device.
1. User Layer
From where the customer stands, using an ATM is simple. They need to present a card and pick a transaction. That wasn’t always the whole story. Inserting a physical card into a reader used to be the only entry point, and that reliance on the magnetic stripe made skimming and shimming, techniques aimed at stealing card data to produce counterfeit copies, a persistent problem for years.
Contactless cards changed the entry point itself. NFC readers now sit alongside traditional card slots on most machines.
A PIN code layers on additional protection against someone using a stolen card. Entry happens through an encrypting PIN pad, a combination of physical keypad and cryptographic module that ensures the PIN never travels or gets stored anywhere in plain text. Verification of the resulting encrypted PIN block happens back at the processing center.
Once identity checks clear, you can withdraw cash, check your balance, transfer funds, and so forth. There’s a full computer running inside the housing, but customers never get anywhere near it directly. Every interaction they have flows through a single banking application running in kiosk mode, locked to full screen.
2. OS Layer
That computer we just mentioned lives inside what’s called the service zone, and this section covers what happens there, setting the cash handling hardware aside for the moment. Physically, the service zone is protected by a thin door and a basic lock. Machines from the same product line frequently share an identical key too, one that’s often available for purchase online with minimal effort.
Beyond the system unit itself, the service zone also houses the ATM’s networking equipment and its wired connections to the card reader, contactless reader, PIN pad, and dispenser, typically running over USB, Ethernet, PCI, or COM interfaces depending on the device.
Windows powers most of these systems, historically through Windows Embedded and increasingly through Windows IoT, a Windows 10 variant built for embedded use.
The kiosk application isn’t the only thing running on that OS. Alongside it sits the ATM’s control software plus a handful of security tools. That can be antivirus protection, Windows AppLocker that keeps unauthorized programs from executing, and a VPN client that maintains a secure tunnel back to the bank’s internal network.
Control software is arguably the most important piece at this layer. Core responsibilities for the control software boil down to managing peripherals and communicating with the processing center, though specific implementations often add more on top of that. Some bundle in software for a monitoring server, letting technicians manage an entire network of self service machines remotely. Others are built in a supervisor mode meant purely for technical staff, offering quick access to diagnostic tools through a hidden menu to simplify physical maintenance visits.
3. Network Layer
Selecting a transaction sets off a verification process handled entirely by the processing center, a server living on the bank’s internal network. That server confirms the card data is legitimate, checks the PIN again before letting the transaction through, rules out any restrictions on the account, and verifies there’s enough balance to cover the request.
Everything exchanged between the ATM and the processing center travels encrypted, usually through a VPN tunnel, protecting against interception or tampering along the way. NDC and DDC are the most common messaging protocols in this exchange, functioning as something of an informal industry standard even before multi-vendor control software became widespread. ISO 8583 and its various offshoots see heavy use as well.
The processing center isn’t the only thing an ATM talks to. Many machines also maintain a connection to a monitoring server used for remote management, health checks, and pushing updates, and unlike the processing center link, this channel frequently runs without any encryption at all.
4. Firmware Layer
Once the processing center signs off, the control software hands things over to the dispenser for a withdrawal, or the deposit module if cash is going in. These components typically sit inside the most fortified section of the ATM, the safe zone, built from tougher materials and secured with its own dedicated key separate from the service zone.
The dispenser counts out the required banknotes from the ATM’s cassettes, moves them into position at the dispensing tray, then opens the shutter, the physical flap that blocks access to the cash until it’s ready. Data moving between the control software and the dispenser can be encrypted, and both sides authenticate one another before any exchange begins, a safeguard against device spoofing. All of that encryption and authentication logic lives directly in the dispenser’s own firmware.
Deposits work differently. Incoming banknotes pass through a validator that checks their authenticity.
ATM Attacks
With the mechanics of an ATM covered, we can turn to the threats themselves. Every attack against these machines falls into one of two broad camps, physical or logical, depending on what the hacker is going after and how they approach it.
Physical attacks go straight after the machine or its components, aiming to extract cash or knock the device out of normal operation without touching a line of code. These predate targeted malware by decades and don’t require much specialized skill. Some don’t even target the machine itself, focusing instead on the people standing in front of it.
Logical attacks operate on a different level entirely. They demand genuine technical skill and preparation, built around exploiting weaknesses in the ATM’s software and network layers. They draw less public attention than physical attacks despite posing a bigger threat to banks, largely because they’re quieter and let a hacker return to the same compromised machine to cash in more than once.
System attacks go after functionality or logic running at the ATM’s OS layer, typically aiming to extract cash or sidestep security controls outright. Black box attacks deserve special attention, where a hacker skips gaining OS access altogether and instead wires their own device directly into the dispenser to control it externally. The same technique can target other peripherals, like the banknote validator.
Network attacks aim at the ATM’s networking components instead, with hackers looking to intercept, forge, or otherwise abuse data in transit, or to seize remote control of the machine. With weak enough safeguards in place, a hacker can forge the responses coming back to the ATM and push through a cash withdrawal even after the processing center rejected it.
Not every attack in this framework ends with cash in hand. A hacker might, say, work to gain remote network access first, then pivot into an OS layer attack from there.
We have seen cases where compromising a single ATM meant compromising the entire bank because there was no network segmentation in place. Conversely, gaining access to the bank’s internal network could provide a path to ATMs and other critical systems connected to it. Credential reuse and a lack of understanding of Active Directory security can lead to devastating consequences in environments like these.
Summary
ATMs have evolved from simple cash dispensers into complex and networked systems. Their security has evolved unevenly alongside them. Physical hardening has made the cash safe itself genuinely difficult to crack, but the service zone housing the control electronics remains comparatively exposed, and that gap has fueled a steady rise in logical attacks. These attacks demand more skill than a physical break-in, but they’re increasingly accessible because of well-documented malware kits.
Cybersecurity is a vast field, and we offer courses covering a wide range of topics, including Active Directory Hacking, Wi-Fi Hacking, Web Application Hacking, SCADA Security, and much more. Our course library is constantly growing as we continue to add new training, all of which is available through our Member Gold plan. If you want unlimited access to our entire training library, including our most advanced courses, consider upgrading to Subscriber Pro.
Lately, we’ve covered several tools you can use with your laptop to track nearby devices and people. While they’re useful, their effectiveness depends on the strength of your Bluetooth adapter, and, of course, you need to have your laptop with you.
This time, we’re doing things differently. We want to show you a device that can automatically monitor nearby devices for extended periods, anywhere you choose to place it, and as often as you want. It doesn’t rely solely on Bluetooth, as it also uses Wi-Fi, which is far more likely to be enabled, increasing the chances of detecting someone in your area.
What is Paxcounter
Paxcounter is an open-source firmware project that takes a cheap little ESP32 development board and turns it into a sensor that can count people. Almost every smartphone in the world is constantly sending out small Wi-Fi signals, called probe requests, and Bluetooth signals too, even when the phone is not connected to anything. Paxcounter listens for these signals in the air. It counts how many different devices it hears during each scan, and from that, it can tell you a real time estimate of how many people are nearby.
The project started out as a simple way to measure how many passengers or pedestrians pass through a certain spot. But over time, it grew into something much bigger. Now it works as a general purpose IoT platform, built on hardware that usually costs somewhere between $10 and $30. Besides its main job of counting Wi-Fi and Bluetooth devices, a Paxcounter can also read environmental sensors, track its GPS position, keep accurate time, and send all of that data out through LoRaWAN, MQTT, a local serial connection, or straight onto an SD card.
How the Counting Works
The way Paxcounter counts people is simple, but it was clearly built with privacy in mind from the very start. Every scan cycle, which lasts 60 seconds by default, the device switches its Wi-Fi and Bluetooth radios into scanning mode and listens for probe requests and advertisement packets coming from nearby devices. Each of these packets carries a MAC address. Paxcounter takes just the last two bytes of that address and turns them into a short, temporary ID. This ID is only used to check for duplicates during that one scan cycle. Once the cycle ends, the count of unique IDs gets sent out, and the whole list is wiped from memory. The firmware also does not try to fingerprint any device. It never tries to figure out a phone’s brand, its operating system, or who owns it. All it wants to know is whether that device has already been counted in the current window.
This scan and clear cycle just keeps repeating, either nonstop or on a schedule if deep sleep power saving is turned on. The results, which include the Wi-Fi count, the Bluetooth count, and sometimes live sensor readings too, get packed into a small payload and sent out through whatever channel the device is set up to use. One thing worth knowing is that Wi-Fi and Bluetooth scanning actually share the same 2.4 GHz radio hardware on the ESP32. So running both scans at the same time slightly lowers the accuracy of each one. Because of that, the project’s own advice is to split Wi-Fi only counting and Bluetooth only counting across two separate devices whenever the best possible accuracy is needed for both.
One Firmware, Many Boards
Paxcounter comes with a hardware abstraction layer and its own pin mapping files for dozens of ESP32 and ESP32-S3 boards. These come from well known manufacturers like LILYGO and TTGO, Heltec, Pycom, WeMos, M5Stack, and Adafruit, and there is also a generic template ready for boards that are not officially supported yet. LILYGO even sells a ready-made board called Paxcounter LoRa, built specifically to run this firmware.
Depending on which board you pick, your device can end up supporting a LoRaWAN radio for sending data over long distances while using very little power, an OLED status screen, or a single color, RGB, or larger LED matrix light to show status. It can also support a physical button for flipping through display pages or sending an alarm message, battery voltage monitoring, GPS positioning, a real time clock chip along with IF482 or DCF77 time telegram output, and even an SD card slot for logging data locally when there is no network around.
Because the whole system was designed to be truly portable, the documentation goes into real detail about power draw, which usually sits somewhere between 450 and 1000 milliwatts depending on how the device is set up. It also makes good use of the ESP32’s deep sleep mode, so a device can keep running for a long stretch of time on just one 18650 lithium ion battery cell. Members of the community have already shared several 3D printable enclosure designs on Thingiverse for the more popular boards.
Getting the Device Up and Running
Paxcounter is built using PlatformIO instead of the plain Arduino IDE. This choice lets it work smoothly with editors like Visual Studio Code, Atom, or Eclipse, and it gives the project reproducible, script driven builds. In fact, the repository runs an automated PlatformIO build check every single time the code changes, using GitHub Actions, and there is even a CodeFactor badge that keeps an eye on ongoing code quality.
The configuration is intentionally spread across a handful of different files instead of being crammed into just one. This keeps board specific settings, behavioral settings, and personal settings nicely separated from each other. The platformio.ini file is where you select which board’s hardware profile you want to compile against. The paxcounter.conf file handles behavioral settings, things like how long a scan cycle lasts, sleep timing, and payload options. The shared lmic_config.h file sets the LoRaWAN region and frequency plan, so it matches the rules where you live. The shared loraconf.h file holds the device’s LoRaWAN join credentials, and the project recommends using OTAA rather than ABP for this. And the shared ota.conf file stores the Wi-Fi credentials the device uses for over the air firmware updates.
You can upload firmware the traditional way, over USB, or once a device has joined a LoRaWAN network, you can push updates over the air instead. A remote command tells the board to connect to Wi-Fi, check a hosted repository called PAX.express for a newer build, and then download and flash it automatically. If anything goes wrong during that process, it will roll back to the previous version on its own. Devices can also be set up to open a small local web based bootstrap menu right when they power on, which lets you upload a firmware file manually, even from a phone in tethering mode, without needing PlatformIO installed on site.
Configuration and Extensibility
Beyond just picking a board, Paxcounter gives you a long list of settings you can tune to fit your needs. It can log environmental data from sensors like the Bosch BMP180, BME280, BMP280, or BME680, read a Nova SDS011 particulate matter sensor to track dust in the air, and keep accurate time using either a DS3231 real time clock or a connected GPS module.
Display and LED
On boards that come with an OLED display, Paxcounter shows live status information you can cycle through with a short press of the button. This includes the current pax count, meaning the people count, a histogram of recent activity, GPS status, environmental sensor readings, and the time of day.
A long press of that same button sends an alarm message out over the network instead, which is a simple way to flag a problem from out in the field without needing any other kind of interface. Even on boards that do not have a display at all, a status LED still tells you what the device is doing through its blink pattern. You get a brief flash whenever a new Wi-Fi or Bluetooth device is spotted, a quick blink while the device is joining the LoRaWAN network, a short blink during data transmission, and a slow, long blink if there is a LoRaWAN stack error. Boards that have an RGB LED get a color coded version of these same signals.
How You Receive the Data
Once a Paxcounter has counted the people nearby and packed everything into a message, that data has to go somewhere so you can actually see it. How that happens depends on which output the device is using, and the good news is you can turn on more than one at the same time. If you are using LoRaWAN, which is the most common setup, the device does not send the data straight to you. Instead, a nearby LoRaWAN gateway picks up the signal first and forwards it on to a network server, usually The Things Stack. There is a small decoder script included with the project, and its job is to take that raw message and turn it into numbers you can actually read, something like a pax count of 14. From there, The Things Stack can pass the data along to your own app or dashboard using MQTT or a webhook, or you can simply watch it come in live through the built in console.
If a board does not have LoRa hardware built in, it can just skip the gateway completely and send that same kind of data straight to an MQTT service over Wi-Fi instead. You can also connect the device to a computer using a USB cable and read the numbers directly from a serial connection. This is a simple way to test things out without needing to set up a network at all. If SD card logging is turned on, everything also gets saved locally as a CSV file, so you can pull the card out later and open it up in a spreadsheet. This comes in handy in places where there is no network coverage to rely on.
Where It’s Used
Because a single Paxcounter device is cheap to build and can be left running unattended for a long time, you will find it popping up in a pretty wide range of places. Retailers and shopping centers use it to measure foot traffic without needing to install cameras. Event organizers use it to watch how crowds move around a venue in real time. Pentesters can get a passive read on how many Wi-Fi and Bluetooth devices are active in a building, or to notice unexpected devices showing up where they shouldn’t, all without needing camera access or network credentials.
Legal and Privacy Considerations
Since Paxcounter’s whole job involves listening to wireless traffic, its documentation is unusually upfront about the legal side of things. It points out that sniffing Wi-Fi and Bluetooth MAC addresses may be regulated or restricted depending on where you live, and it links to specific starting references for the US, the UK, the Netherlands and the EU, and Germany. It also makes clear that the legal responsibility for how a device is built and deployed falls on the person doing it, especially for public deployments where the results might get published somewhere. On the technical side of privacy, the project’s own design actually holds up pretty well against that legal backdrop. Identifiers are only ever built from the last two bytes of a scanned MAC address, they are kept in memory just for the length of one scan cycle, and then they are discarded completely. No MAC addresses or identifiers are ever sent out over the network, and the firmware does not do any extra tracking or fingerprinting of the devices it scans.
Summary
What really makes Paxcounter stand out is not any single feature on its own. It is the whole combination working together. One piece of open source firmware supports dozens of cheap boards, runs for a long time on a small battery, counts people without saving anything identifying about them, doubles as a general environmental sensor node, speaks LoRaWAN, MQTT, serial, and SD card all at once, and can be fully reconfigured from a distance once it is out in the field. The full source code, the complete board list, and all the documentation are available on GitHub.
If you enjoy experimenting with frequencies and trying new things, we recommend signing up for our SDR for Hackers training. With Master OTW, you’ll learn how to use your computer and inexpensive SDR hardware to explore and hack a wide range of radio signals.
This is the final article of our Drone Warfare series on Ukraine’s rise as a drone powerhouse. But Ukraine’s success story is not one it achieved alone. The country’s drone industry was built with the support of partners from around the world who helped Ukraine during its most difficult times. Here we look at Ukraine’s export strategy and how it can serve as a way to give back by sharing hard-earned battlefield experience and technology with the nations that helped make this success possible.
Battlefield Experience
For most of the war, Ukraine’s drone sector existed on the demand side of the defense market. The country needed huge volumes of FPV drones, interceptor drones and reconnaissance systems simply to keep pace with the battlefield. By 2026, that position began to change. Ukraine started to present itself not only as a state that needed drones, but as a state that could supply them, co-produce them, and teach others how to use them. In March 2026 President Volodymyr Zelenskiy discussed joint arms production with Dutch Prime Minister Rob Jetten and said Ukraine was ready to export interceptor drones that are not needed on its own battlefield.
Interceptor drones and the latest AI developments. Source: Ukraine’s Arm Monitor
Ukraine is not trying to sell a platform developed in peacetime and polished for foreign buyers. It is offering weapons and systems that were shaped by daily combat against a technologically capable enemy. That gives Ukrainian exports a different value proposition. They are presented as battlefield-tested tools that have already survived the hardest possible proving ground.
The Export Model
Ukraine’s export strategy depends on the fact that it is producing more than it can immediately absorb on the front line in certain categories, especially interceptor drones. In June 2026 Ukraine said it could produce 2,000 interceptor drones per day, with about half potentially available beyond domestic needs, and that it could supply at least 1,000 interceptor drones a day to allies facing Shahed attacks if investment improves. That is the logic behind the export conversation. Ukraine is not opening the floodgates on every weapon it makes. It is identifying categories where production has moved beyond immediate domestic consumption.
Business Insider also reported that Ukraine wants to protect its own security first and only share technologies that do not compromise its battlefield position. That means exports are likely to focus on systems that are already partially superseded on the Ukrainian front, or on systems that can be co-produced under controlled conditions.
Europe
Europe is the most obvious destination for Ukraine’s export strategy because the continent is already moving in Ukraine’s direction. The Netherlands are going to spend €248 million on drones for Ukraine, with production split between the Netherlands and Ukraine. On 17 June 2026 the Netherlands pledged another €500 million for drones and air defense equipment. These are signs that European governments are beginning to fund drone production as an industrial activity.
The Drone Squad Fury unmanned aerial platform developed by OM Defense Systems on display at the Eurosatory defense exhibition in Paris, June 2026. Source: Militarnyi
The broader European defense picture points the same way. It was reported that G7 countries and the United States had agreed to allow Ukraine-based and European firms to produce long-range missiles and air defense systems under license. Europe is no longer only buying Ukrainian results, it wants to buy into the production model behind them.
Source: Airbus’ drone portfolio
The broader European defense market is also moving in Ukraine’s direction. For instance, Airbus partnered with the French counter-drone startup Alta Ares. Under the June 2026 memorandum of understanding, Airbus will integrate Alta Ares’ AI-guided interceptors, including the Black Bird and X-Lock systems, both combat-tested in Ukraine since 2024, into its Fortion IBMS command-and-control platform, connecting Alta Ares’ targeting software and interceptor drones to Airbus’ battle management systems to create a sensor-to-shooter chain against drone and cruise missile threats.
Middle East
The Middle East is the second major market because it faces a different but equally urgent drone threat. In March 2026 Zelenskiy said Ukraine was ready to send instructors to the Middle East and export interceptor drones that are not needed at home. Business Insider added that Ukrainian officials see older Ukrainian counter-drone technology as still useful for allies facing Shahed attacks, even if those systems are already outdated by Ukraine’s own battlefield standards. A weapon does not need to be the newest model to be valuable if the user’s threat environment is less intense than Ukraine’s.
Ukrainian interceptor drone in open terrain (desert-like background works well for the Middle East angle)
That makes the Middle East a natural fit for Ukraine’s export model because the buyer often wants a system, not just a drone. The package includes interceptor drones, training, radar integration, and electronic warfare resilience. Zelenskiy explicitly framed the issue that way, saying that without radar coverage and software that can operate under jamming, an interceptor is not a real defender.
Production
The most interesting part of Ukraine’s export strategy is not the sale itself. It is the move toward co-production. The point of co-production is to make exports more durable and less vulnerable to disruption. It also lets allies develop industrial capacity while Ukraine keeps access to the newest combat-tested designs. The G7 agreement reported by The Guardian shows a model where production can be shifted into partner territory while still drawing on Ukrainian experience and requirements. That approach helps solve three problems at once. It spreads risk away from the battlefield. It makes procurement faster for partners. And it creates a legal framework for sharing sensitive technology without handing over full control of the most advanced systems.
The Financial Logic
The export strategy also has a budget logic. Drone exports and co-production can help bring in foreign money, expand industrial capacity, and reduce pressure on the domestic defense budget. The Netherlands’ funding would support drones and air defense equipment for Ukraine, while Ukraine’s officials see export volume as a way to unlock more production capacity. The practical idea is that external orders help keep factories busy, while revenue and investment help scale the next generation of systems.
Ukraine’s Drone Industry arrives in Düsseldorf. Source: DroneXL
This logic is important in wartime because the domestic state cannot fund every possible expansion on its own. Exports make production more sustainable. They also let Ukraine distribute risk across several partners rather than relying only on its own budget and wartime aid flows. In other words, the export strategy is partly about money, but it is also about industrial resilience.
Main Constraints
Ukraine’s export strategy is still tightly constrained by its own security needs. Ukrainian officials want to keep priority for domestic forces and treat exports as selective. That means the country is not trying to become a free-market weapons bazaar in the middle of a war. It is trying to manage surplus capacity without weakening the front line. There is also the issue of sensitivity. Not every system can be exported, and not every partner can receive the same level of access. Licensed production in allied countries solves part of that problem, but only part. The more advanced the system, the more likely it is to remain under stricter Ukrainian control. That is why the export strategy is likely to be layered. That means some hardware is going to be sold directly, while some systems will be co-produced, some software and training will be shared for integration, and some capabilities will stay in-house.
Strategic Value
Ukraine’s biggest advantage in the export market is not price alone. It is combat credibility. Allies are interested because Ukraine’s drones and counter-drone systems were developed in the harshest possible environment. A state that has spent years fighting under heavy electronic warfare pressure, missile strikes, and mass drone attacks has something to offer that many peacetime defense industries do not. That does not mean Ukraine will dominate global drone exports. Competition is still strong, and certification with production security all remain real obstacles. But the country has already crossed an important threshold, where it’s no longer only asking for help. It is now a partner that can supply systems, share production, and train others to fight the same kind of war.
Conclusion
Europe wants production. The Middle East wants interception. Ukraine wants revenue and industrial depth. That creates a new model built around selective exports and battlefield-tested expertise. Ukraine is no longer only defending itself with drones, but it is using drone expertise to build alliances. That is the meaning of its export strategy today.
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