It's no secret that Milwaukee is one of the most popular tool brands, and while many owners love the M18 line of powerful 18V tools, Milwaukee's M12 platform is equally excellent at a lower price point. If you're looking to get your money's worth with a new tool purchase, here are five M12 tools that live up to the hype.
Do you have any old, outdated gas-powered tools you'd like to give a new lease on life? If so, Makita has a neat new product you'll absolutely love. Makita is launching a 40V max XGT electric motor unit, which is a 25 to 50cc gas engine replacement electric motor you can drop in, bolt on, and go.
Microsoftโs new winapp CLI simplifies Windows app development with one-command setup, faster testing, and easier packaging.
The post Microsoft Launches winapp to Simplify Windows App Development appeared first on TechRepublic.
Microsoftโs new winapp CLI simplifies Windows app development with one-command setup, faster testing, and easier packaging.
The post Microsoft Launches winapp to Simplify Windows App Development appeared first on TechRepublic.
AI coding work is rising fast, but the biggest payoff isnโt evenly shared. A Science analysis suggests seasoned developers get stronger gains than newcomers, which could reshape how you learn, interview, and prove value.
The post AI coding work is shifting fast, and your career path may split appeared first on Digital Trends.
DeWALT is a popular brand among enthusiasts and professionals thanks to its wide array of tools, with more arriving all the time. If you have a few DeWALT 20V tools and battery packs and go to buy another tool, you'll see models like the 20V MAX, XR, and Atomicโbut what does that actually mean?
Volume is one of the most widely used metrics in trading. Every crypto trader, from beginner to professional, has stared at the green and red bars under their chart trying to decode marketย intent.
But hereโs the uncomfortable truth:
Most traders are reading the wrong volume.
Or worseโโโtheyโre reading it in the wrongย context.
This is especially true when it comes to the popular Daily 24h Volume indicator. Youโve probably seen it on exchanges like Binance, Bybit, OKXโโโand on TradingView indicators that attempt to emulateย it.
And while the metric sounds intuitive (โhow much volume traded in the last 24hโ), itโs often misunderstood and misapplied in liveย trading.
In this article, I want to breakย down:
Letโs start with theย basics.
Daily 24h Volume Indicator is attractive because:
For example:
Itโs a macro-level liquidity gauge.
But hereโs theย problem:
Daily 24h volume does NOT tell you whatโs happening right now on your candle. It tells you what happened in the past day, smoothed into one enormous rolling window. This introduces several pitfalls.
Daily 24 volume cannot show momentum shifts inside a candle. You might think volume is increasingโฆ But itโs actually just updating the rollingย window.
It blends all buy/sell pressure, spikes, and micro-movements into one bigย number.
You miss:
Because it covers the full 24h window, it behaves like a movingย average:
But the bar forming RIGHT NOW couldย have:
โ orย โ
This disconnect confuses decision-making.
Below is a simplified comparison to set things straight.
In short:
Most traders mix these two conceptsโโโand get confused signals as aย result.
After years of active crypto trading, I realized Iย needed:
This led me to develop the Advanced Volume Suiteโโโa tool that merges the strengths of bothย worlds:
Itโs the volume engine I personally use in my trading, and now Iโm sharing it publicly.
The next section describes how itย works.
The Advanced Volume Suite is a multi-layered volume analysis system designed for traders who rely on volume as a primary decision driver. It expands far beyond TradingViewโs standard volume bars byย adding:
All volume is converted into USDT value (volume ร close) to normalize activity across increasing or decreasing prices.
The indicator calculates a custom 24h rolling volume, just like Binance and Bybitย display.
A powerful ratio that measures momentum inside eachย bar.
Identifies abnormal activityย using:
Detects:
The indicator introduces intelligent volume bar coloring, which improves clarity and helps interpret orderflow visually:
Green = close > open
Red = close < open
(Like standard volume but using USDTย values)
Colors only when candle body is strong relative to its range.
Filters noise and highlights meaningful bars.
Detects โaggressiveโ buyers or sellers basedย on:
This indicator bridges the gapย between:
And wraps itย into:
It replaces multiple tools and simplifies your volume-based decision-making.
Volume is one of the most important trading metricsโโโbut only when interpreted correctly.
If youโve ever missed a breakout, failed to see a spike, or misjudged the strength behind a move, this suite gives you the clarity you wereย missing.
This indicator is fully free and open-source on TradingView, so that traders can review and verity its functionality.
Advanced Volume Suite (24h, Pulse, Spikes, Breakout Pressure)โโโIndicator by zalutskyiyuriyโโโTradingView
Why Most Traders Misread Volume: A Deep Dive into Standard Volume vs Daily 24h Volume was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.
The numbers tell a stark story: $1.42 billion lost across 149 documented incidents in 2024 due to smart contract vulnerabilities, with access control flaws accounting for $953.2 million in damages alone. While the Web3 community debates the perfect AI solution for smart contract security, billions continue to drain from protocols that could have been protected..
The post Why Smart Contract Security Canโt Wait for โBetterโ AI Models appeared first on Security Boulevard.
An open-source Android application designed to identify and test devices vulnerable to CVE-2025-36911, a critical authentication bypass flaw in Googleโs Fast Pair Bluetooth protocol. The vulnerability, commonly referred to as WhisperPair, affects millions of Bluetooth audio devices worldwide, enabling unauthorised pairing and potentially granting access to microphoneswithout user consent. CVE-2025-36911 represents a significant cryptographic weakness [โฆ]
The post WPair Scanner Released to Detect WhisperPair Flaw in Googleโs Fast Pair Protocol appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform.
If you've ever used a 3D printer, you may recall the wondrous feeling when you first printed something you could have never sculpted or built yourself. Download a model file, load some plastic filament, push a button, and almost like magic, a three-dimensional object appears. But the result isn't polished and ready for mass production, and creating a novel shape requires more skills than just pushing a button. Interestingly, today's AI coding agents feel much the same way.
Since November, I have used Claude Code and Claude Opus 4.5 through a personal Claude Max account to extensively experiment with AI-assisted software development (I have also used OpenAI's Codex in a similar way, though not as frequently). Fifty projects later, I'll be frank: I have not had this much fun with a computer since I learned BASIC on my Apple II Plus when I was 9 years old. This opinion comes not as an endorsement but as personal experience: I voluntarily undertook this project, and I paid out of pocket for both OpenAI and Anthropic's premium AI plans.
Throughout my life, I have dabbled in programming as a utilitarian coder, writing small tools or scripts when needed. In my web development career, I wrote some small tools from scratch, but I primarily modified other people's code for my needs. Since 1990, I've programmed in BASIC, C, Visual Basic, PHP, ASP, Perl, Python, Ruby, MUSHcode, and some others. I am not an expert in any of these languagesโI learned just enough to get the job done. I have developed my own hobby games over the years using BASIC, Torque Game Engine, and Godot, so I have some idea of what makes a good architecture for a modular program that can be expanded over time.
ยฉ Aurich Lawson | Getty Images
Security researchers and penetration testers gain a comprehensive open-source reconnaissance platform with the release of Argus v2.0, a Python-based information gathering toolkit that consolidates 135 specialised modules into a unified command-line interface. The toolkit addresses the growing complexity of modern attack surface management by providing integrated access to network mapping, web application analysis, and threat [โฆ]
The post Argus: Python-Based Recon Toolkit Aims to Boost Security Intelligence appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform.
A new Harmonic Security report reveals a sharp rise in sensitive data shared with generative AI tools like ChatGPT, increasing the risk of security breaches, compliance violations, and data exposure across global organizations.
The post Report: Massive Amounts of Sensitive Data Being Shared with GenAI Tools appeared first on Security Boulevard.
Welcome back, aspiring digital forensics investigators!
AnyDesk first appeared around 2014 and very quickly became one of the most popular tools for legitimate remote support and system administration across the world. It is lightweight, fast, easy to deploy. Unfortunately, those same qualities also made it extremely attractive to cybercriminals and advanced persistent threat groups. Over the last several years, AnyDesk has become one of the preferred tools used by attackers to maintain persistent access to compromised systems.
Attackers abuse AnyDesk in a few different ways. Sometimes they install it directly and configure a password for unattended access. Other times, they rely on the fact that many organizations already have AnyDesk installed legitimately. All the attacker needs to do is gain access to the endpoint, change the AnyDesk password or configure a new access profile, and they now have quiet, persistent access. Because remote access tools are so commonly used by administrators, this kind of persistence often goes unnoticed for days, weeks, or even months. During that time the attacker can come and go as they please. Many organizations do not monitor this activity closely, even when they have mature security monitoring in place. We have seen companies with large infrastructures and centralized logging completely ignore AnyDesk connections. This has allowed attackers to maintain footholds across geographically distributed networks until they were ready to launch ransomware operations. When the encryption finally hits critical assets and the cryptography is strong, the damage is often permanent, unless you have the key.
We also see attackers modifying registry settings so that the accessibility button at the Windows login screen opens a command prompt with the highest privileges. This allows them to trigger privileged shells tied in with their AnyDesk session while minimizing local event log traces of normal login activity. We demonstrated similar registry hijacking concepts previously in โPowerShell for Hackers โ Basics.โ If you want a sense of how widespread this abuse is, look at recent cyberwarfare reporting involving Russia.
Kaspersky has documented numerous incidents where AnyDesk was routinely used by hacktivists and financially motivated groups during post-compromise operations. In the ICS-CERT reporting for Q4 2024, for example, the โCrypt Ghoulsโ threat actor relied on tools like Mimikatz, PingCastle, Resocks, AnyDesk, and PsExec. In Q3 2024, the โBlackJackโ group made heavy use of AnyDesk, Radmin, PuTTY and tunneling with ngrok to maintain persistence across Russian government, telecom, and industrial environments. And thatโs just a glimpse of it.
Although AnyDesk is not the only remote access tool available, it stands out because of its polished graphical interface and ease of use. Many system administrators genuinely like it. That means you will regularly encounter it during investigations, whether it was installed for legitimate reasons or abused by an attacker.
With that in mind, letโs look at how to perform digital forensics on a workstation that has been compromised through AnyDesk.
Today we are going to focus on the types of log files that can help you determine whether there has been unauthorized access through AnyDesk. These logs can reveal the attackerโs AnyDesk ID, their chosen display name, the operating system they used, and in some cases even their IP address. Interestingly, inexperienced attackers sometimes do not realize that AnyDesk transmits the local username as the connection name, which means their personal environment name may suddenly appear on the victim system. The logs can also help you understand whether there may have been file transfers or data exfiltration.
For many incident response cases, this level of insight is already extremely valuable. On top of that, collecting these logs and ingesting them into your SIEM can help you generate alerts on suspicious activity patterns such as unexpected night-time access. Hackers prefer to work when users are asleep, so after-hours access from a remote tool should always trigger your curiosity.
Here are the log files and full paths that you will need for this analysis:
LoginC:\Users\%username%\AppData\Roaming\AnyDesk\ad.trace
C:\Users\%username%\AppData\Roaming\AnyDesk\connection_trace.txt
C:\ProgramData\AnyDesk\ad_svc.trace
C:\ProgramData\AnyDesk\connection_trace.txtAnyDesk can be used in two distinct ways. The first is as a portable executable. In that case, the user runs the program directly without installing it. When used this way, the logs are stored under the userโs AppData directory. The second way is to install AnyDesk as a service. Once installed, it can be configured for unattended access, meaning the attacker can log in at any time using only a password, without the local user needing to confirm the session. When AnyDesk runs as a service, you should also examine the ProgramData directory as it will contain its own trace files. The AppData folder will still hold the ad.trace file, and together these files form the basis for your investigation.
With this background in place, letโs begin our analysis.
The connection_trace.txt logs are relatively readable and give you a straightforward record of successful AnyDesk connections. Here is an example with a randomized AnyDesk ID:
Incoming 2025โ07โ25, 12:10 User 568936153 568936153
The real AnyDesk ID has been redacted. What matters is that the log clearly shows there was a successful inbound connection on 2025โ07โ25 at 12:10 UTC from the AnyDesk ID listed at the end. This already confirms that remote access occurred, but we can dig deeper using the other logs.
Now we move into the part of the investigation where we begin to understand who our attacker might be. Although names, IDs, and even operating systems can be changed by the attacker at any time, patterns still emerge. Most attackers do not constantly change their display name unless they are extremely paranoid. Even then, the timestamps do not lie. Remote logins occurring repeatedly in the middle of the night are usually a strong indicator of unauthorized access.
We will work primarily with the ad.trace and ad_svc.trace files. These logs can be noisy, as they include a lot of error messages unrelated to the successful session. A practical way to cut through the noise is to search for specific keywords. In PowerShell, that might look like this:
PS > get-content .\ad.trace | select-string -list 'Remote OS', 'Incoming session', 'app.prepare_task', 'anynet.relay', 'anynet.any_socket', 'files', 'text offers' | tee adtrace.log
PS > get-content .\ad_svc.trace | select-string -list 'Remote OS', 'Incoming session', 'app.prepare_task', 'anynet.relay', 'anynet.any_socket', 'files', 'text offers' | tee adsvc.log
These commands filter out only the most interesting lines and save them into new files called adtrace.log and adsvc.log, while still letting you see the results in the console. The tee command behaves this way both in Windows and Linux. This small step makes the following analysis more efficient.
In many cases, the ad_svc.trace log contains the external IP address from which the attacker connected. You will often see it recorded as โLogged in from,โ alongside the AnyDesk ID listed as โAccepting from.โ For the sake of privacy, these values were redacted in the screenshot we worked from, but they can be viewed easily inside the adsvc.log file you created earlier.
Once you have the IP address, you can enrich it further inside your SIEM. Geolocation, ASN information, and historical lookups may help you understand whether the attacker used a VPN, a hosting provider, a compromised endpoint, or even their home ISP.
Inside ad.trace you will generally find the attackerโs display name in lines referring to โIncoming session request.โ Right next to that field you will see the corresponding AnyDesk ID. You may also see references to the attackerโs operating system.
In the example we examined, the attacker was connecting from a Linux machine and had set their display name to โIT Depโ in an attempt to appear legitimate. As you can imagine, users do not always question a remote session labeled as IT support, especially if the attacker acts confidently.
AnyDesk does not only provide screen control. It also supports file transfer both ways. That means attackers can upload malware or exfiltrate sensitive company data directly through the session. In the ad.trace logs you will sometimes see references such as โPreparing files in โฆโ which indicate file operations are occurring.
This line alone does not always tell you what exact files were transferred, especially if the attacker worked out of temporary directories. However, correlating those timestamps with standard Windows forensic artifacts, such as recent files, shellbags, jump lists, or server access logs, often reveals exactly what the attacker viewed or copied. If they accessed remote file servers during the session, those server logs combined with your AnyDesk timestamps can paint a very clear picture of what happened.
In our case, the attacker posing as the โIT Depโ accessed and exfiltrated files stored in the Documents folder of the manager who used that workstation.
Given how widespread AnyDesk is in both legitimate IT environments and malicious campaigns, you should always consider it a high-priority artifact in your digital forensics and incident response workflows. Make sure the relevant AnyDesk log files are consistently collected and ingested into your SIEM so that suspicious activity does not go unnoticed, especially outside business hours. Understanding how to interpret these logs shows the attackerโs behavior that otherwise feels invisible.
Our team strongly encourages you to remain aware of AnyDesk abuse patterns and to include them explicitly in your investigation playbooks. If you need any support building monitoring, tuning alerts, or analyzing remote access traces during an active case, we are always happy to help you strengthen your security posture.
์คํธ๋กํฝ์ ํด๋ก๋ ์ฝ๋์ ๊ธฐ๋ฅ์ ํ๋ก๊ทธ๋๋ฐ ์์ญ์ ๋์ด ์ผ์์ ์ธ ๊ธฐ์ ์ ๋ฌด ํ๋ฆ์ผ๋ก ํ์ฅํ๊ธฐ ์ํ โ์ฝ์์ปค(Cowork)โ๋ฅผ ํ๋ฆฌ๋ทฐ ๋ฒ์ ์ผ๋ก 12์ผ ๊ณต๊ฐํ๋ค.
์ด ์๋ก์ด ์ฝ๋ฉ ์ด์์คํดํธ๋ ์กฐ์ง์ด ํน์ ํด๋์ ๋ํ ์ ๊ทผ ๊ถํ์ ๋ถ์ฌํ ๊ฒฝ์ฐ ์ผ์ ์์ฝ, ๋ณด๊ณ ์ ์์ฑ, ํ์ผ ์ ๋ฆฌ์ ๊ฐ์ ์์ ์ ์๋ํํ ์ ์๋๋ก ์ง์ํ๋ค. ์ฝ์์ปค๋ ๊ด๋ จ ๋๊ตฌ, ๋ฐ์ดํฐ๋ฒ ์ด์ค, ์ ํ๋ฆฌ์ผ์ด์ ๊ณผ์ ์ฐ๋๋ ๊ฐ๋ฅํ๋ค.
๋ํ ํฌ๋กฌ ํ๊ฒฝ์์ ํด๋ก๋์ ํจ๊ป ์ฌ์ฉํ๋ฉด ๋ธ๋ผ์ฐ์ ์ ๊ทผ์ด ํ์ํ ์์ ๋ ์ํํ ์ ์๋ค. ์คํธ๋กํฝ์ ๊ณต์ ๋ธ๋ก๊ทธ๋ฅผ ํตํด ์ฌ์ฉ์๊ฐ AI ๊ธฐ๋ฐ ์ด์์คํดํธ๊ฐ ํ๋์ ์์ ์ ๋ง์น ๋๊น์ง ๊ธฐ๋ค๋ฆฌ์ง ์๊ณ ์ฌ๋ฌ ์์ ์ ๋ณ๋ ฌ๋ก ํ ๋นํ ์ ์๋ค๊ณ ์ค๋ช ํ๋ค.
์ ๋๋ฆฌ์คํธ๋ค์ ์ฝ์์ปค์ ๋์ ์ด AI ์ด์์คํดํธ๋ฅผ ๋ณด๋ค ๋ค์ํ ๋น์ฆ๋์ค ๊ธฐ๋ฅ์ ํ์ฉํ๋ ค๋ ์คํธ๋กํฝ์ ์ ๋ต์ ๋ฐฉํฅ์ฑ์ ๋ณด์ฌ์ค๋ค๊ณ ๋ถ์ํ๋ค.
์ปจ์คํ ๊ธฐ์ ์๋ฒ ๋ ์คํธ ๊ทธ๋ฃน์ ์ด๊ด ์ ๋๋ฆฌ์คํธ ๋ฒ ๋ฅด์ํ ์ค๋ฆฌ๋ฐ์คํ๋ฐ๋ โ์ฝ์์ปค๋ ๋จ์ํ ๋ํ๋ฅผ ๋์ด ๋ฒ์๊ฐ ์ ํ๋ ์คํ ์ค์ฌ ๊ธฐ๋ฅ์ผ๋ก ํ์ฅํจ์ผ๋ก์จ, ์ง์ ๊ธฐ๋ฐ ์ญํ ์์ ์ฃผ๋ฅผ ์ด๋ฃจ๋ ๋ฌธ์ ๋ฐ ํ์ผ ์ค์ฌ ์ ๋ฌด์ ํด๋ก๋๋ฅผ ์ค์ง์ ์ผ๋ก ํ์ฉํ๋ ค๋ ์๋๋ฅผ ๋ฐ์ํ๋คโ๋ผ๊ณ ์ค๋ช ํ๋ค.
์ค๋ฆฌ๋ฐ์คํ๋ฐ๋ ์ด์ด ๊ฐ๋๋ ์ผ์ ๋ช ํํ๊ฒ ์ค์ ํ ์ ์๋ ๋ฆฌ์์น, ํ๋ก์ ํธ ๊ด๋ฆฌ ์กฐ์ง(PMO), ์ด์, ๋ถ์๊ณผ ๊ฐ์ ์ญํ ์์๋ ์๋ก์ด ๋๊ตฌ์ ํจ๊ณผ๋ฅผ ๊ธฐ๋ํ ์ ์์ผ๋ฉฐ, ์ด๋ฌํ ์์ญ์์ ๋์ ์ด ๊ฐ์ฅ ํ๋ฐํ๊ฒ ์ด๋ค์ง ๊ฐ๋ฅ์ฑ์ด ๋๋ค๊ณ ์ ๋งํ๋ค.
์ปจ์คํ ๊ธฐ์ ํจ์ฒ๋ผ๊ทธ๋ฃน์ ๋ฐ์ดํฐยทAIยท์ธํ๋ผ ๋ถ๋ฌธ ์ด๊ด ๋ธ๋๋ค๋ฆฌ ์ฌ๋ฏผ ์ญ์ ๊ฐ์ ๊ฒฌํด๋ฅผ ๋ณด์ด๋ฉฐ, ์ฝ์์ปค๊ฐ ๊ฐ๋ฐ์์๊ฒ๋ ์ ์ฉํ ์ ์๋ค๊ณ ์ธ๊ธํ๋ค. ์ฌ๋ฏผ์ ์ฝ์์ปค๋ฅผ ์คํธ๋กํฝ์ โ์ปดํจํฐ ์ฌ์ฉ(computer-use)โ ๊ธฐ๋ฅ๊ณผ ์ปค๋งจ๋๋ผ์ธ ์ ํธ๋ฆฌํฐ๊ฐ ์์ฐ์ค๋ฝ๊ฒ ์งํํ ๊ฒฐ๊ณผ๋ก ํ๊ฐํ๋ค.
์ฝ์์ปค๋ ๋ธ๋ผ์ฐ์ ๋ฅผ ํตํด ์์คํ ํ๋ฉด์ ์ดํด๋ณด๊ฑฐ๋ ์คํฌ๋ฆฐ์ท์ ์ฐ๋ ๋ฐฉ์์ด ์๋๋ผ ์ด์์ฒด์ ์ ํต์ฌ ๊ธฐ๋ฅ์ ์ง์ ์ ๊ทผํ ์ ์๊ธฐ ๋๋ฌธ์, ์์ด์ ํธ ๊ธฐ๋ฐ ์ํํธ์จ์ด ๊ฐ๋ฐ ์ํฌํ๋ก ์ธ์ ์์ญ์ ์์นํ ์์ ์ ์๋ํํ๊ณ ์ด์ ๋จ๊ณ๋ก ํ์ฅํ๋ ๋ฐ ํ์ฉํ ์ ์๋ค๋ ์ค๋ช ์ด๋ค.
์ฌ๋ฏผ์ ์๋ก โํ๋ก์ ํธ์ ์ผ๋ถ์ธ JSON ๋ฐ์ดํฐ๋ฅผ ๋น ๋ฅด๊ฒ ๋งํฌ๋ค์ด ํ์์ผ๋ก ๋ณํํด ๋น๊ฐ๋ฐ์๋ ํด๋น ์ ๋ณด๋ฅผ ์ฝ๊ฒ ์ฝ์ ์ ์๋๋ก ๋ง๋๋ ์์ โ์ ๋ค์๋ค.
๋ค๋ง ์คํธ๋กํฝ์ ์ฝ์์ปค์ ์์คํ ์ด๋ ํ๊ฒฝ ์ ๊ทผ ๊ถํ์ ๋ถ์ฌํ ๊ฒฝ์ฐ ์ฃผ์๊ฐ ํ์ํ๋ค๊ณ ๊ฒฝ๊ณ ํ๋ค. ํ๋กฌํํธ๋ฅผ ์๋ชป ์ดํดํด ํ์ผ ์ญ์ ์ ๊ฐ์ ํ๊ดด์ ์ธ ๋ช ๋ น์ ์คํํ ์ ์๊ธฐ ๋๋ฌธ์ด๋ค. ๋ค๋ง ๋ช ๋ น์ด๋ ์์ ์ ์คํํ๊ธฐ ์ ์๋ ์ฌ์ฉ์์๊ฒ ํ์ธ์ ์์ฒญํ๋๋ก ์ค๊ณ๋ผ ์๋ค๊ณ ๋ฐํ๋ค.
๋ํ ์ ์ฑ ์ฝํ ์ธ ๊ฐ ๋๊ตฌ์ ๋ด์ฅ๋ ๋ฐฉ์ด ์ฒด๊ณ๋ฅผ ์ฐํํด ํด๋ก๋์ ๊ณํ์ ๋ณ๊ฒฝํ ์ ์๋ ํ๋กฌํํธ ์ธ์ ์ ๊ณต๊ฒฉ ์ํ๋ ํจ๊ป ์ง์ ํ๋ค.
๋ ๋ค๋ฅธ ์ปจ์คํ ๊ธฐ์ ๋ฌด์ด์ธ์ฌ์ดํธ์ค๋์คํธ๋ํฐ์ง์ ์์ ์ ๋๋ฆฌ์คํธ ์ ์ด์จ ์ค๋์จ์ ์ด๋ฌํ ๋ฌธ์ ๋ฅผ ์ํํ๊ธฐ ์ํด, ์ ํ์ด ์ ์ ์ถ์๋ ๋ ํ์ผ ์ญ์ ์ ๋ณต๊ตฌํ ์ ์๊ฑฐ๋ ์ด๋ฉ์ผ ์ ์ก์ ์ทจ์ํ ์ ์๋ ๋๋๋ฆฌ๊ธฐ ๊ธฐ๋ฅ์ ์ถ๊ฐํ ์ ์๋ค๊ณ ์ ์ํ๋ค.
์ค๋์จ์ ์ด ๊ธฐ๋ฅ์ด ํ๋กฌํํธ ์ธ์ ์
๊ณต๊ฒฉ๊ณผ ์ฌ์ฉ์ ์ค์ ๋ชจ๋๋ฅผ ๋ณด์ํ ์ ์์ ๊ฒ์ด๋ผ๊ณ ๋ถ์ํ๋ค. ํ์ฌ ์ด ์๋ก์ด ํํ์ ์ด์์คํดํธ๋ ๋งฅOS ์ ํ๋ฆฌ์ผ์ด์
์ ํตํด ํด๋ก๋ ๋งฅ์ค ๊ตฌ๋
์์๊ฒ ์ ๊ณต๋๊ณ ์๋ค.
dl-ciokorea@foundryco.com
์ฃผ์ ๋ฐ์ด๋ธ ์ฝ๋ฉ ํ๋ซํผ์ด ํํ ์ฌ์ฉ๋๋ ํ๋ก๊ทธ๋๋ฐ ํ๋กฌํํธ์ ๋ํด ์์ ํ์ง ์์ ์ฝ๋๋ฅผ ๋ฐ๋ณต์ ์ผ๋ก ์์ฑํ๊ณ , ์ด ๊ณผ์ ์์ โ์น๋ช ์ โ ์์ค์ผ๋ก ํ๊ฐ๋๋ ์ทจ์ฝ์ ๊น์ง ๋ง๋ค์ด๋ธ๋ค๋ ํ ์คํธ ๊ฒฐ๊ณผ๊ฐ ๋์๋ค.
๋ณด์ ์คํํธ์ ํ ์์ด๋ ์ด๋ค ๋๊ตฌ๊ฐ ์ ํํ๋ ๊ท์น์ด๋ ๊ดํ์ผ๋ก ๋์ํ ์ ์๋ ๋ณด์ ๊ฒฐํจ์ ๋น๊ต์ ์ ํํผํ์ง๋ง, ์์ ๊ณผ ์ํ์ ๊ฐ๋ฅด๋ ๊ธฐ์ค์ด ์ํฉ์ ๋ฐ๋ผ ๋ฌ๋ผ์ง๋ ์์ญ์์๋ ์ด๋ ค์์ ๊ฒช๋๋ค๊ณ ์ค๋ช ํ๋ค.
ํ ์์ด๋ 2025๋ 12์ ์งํํ ์ด๋ฒ ํ๊ฐ์์ ํด๋ก๋ ์ฝ๋(Claude Code), ์คํAI ์ฝ๋ฑ์ค(OpenAI Codex), ์ปค์(Cursor), ๋ ํ๋ฆฟ(Replit), ๋ฐ๋น(Devin) ๋ฑ ์ฃผ์ ๋ฐ์ด๋ธ ์ฝ๋ฉ ๋๊ตฌ 5์ข ์์ ์ฌ์ ์ ์๋ ํ๋กฌํํธ๋ฅผ ์ฌ์ฉํด 3๊ฐ์ง ํ ์คํธ ์ ํ๋ฆฌ์ผ์ด์ ์ ๊ตฌ์ถํ๋ ๋ฐฉ์์ผ๋ก ๋น๊ต ๋ถ์ํ๋ค.
๊ทธ ๊ฒฐ๊ณผ, 5๊ฐ ๋๊ตฌ๊ฐ ๊ฐ๊ฐ 3๊ฐ์ฉ ์์ฑํ ์ด 15๊ฐ ์ ํ๋ฆฌ์ผ์ด์ ์ ์ฝ๋์์ ๋ชจ๋ 69๊ฐ์ ์ทจ์ฝ์ ์ด ๋ฐ๊ฒฌ๋๋ค. ์ด ๊ฐ์ด๋ฐ ์ฝ 45๊ฐ๋ โ๋ฎ์~์ค๊ฐโ ์์ค์ ์ฌ๊ฐ๋๋ก ํ๊ฐ๋์ง๋ง, ๋๋จธ์ง ๋ค์๋ โ๋์โ์ผ๋ก ๋ถ๋ฅ๋๋ค. ๊ทธ์ค 6๊ฐ๋ โ์น๋ช ์ โ ์ทจ์ฝ์ ์ ํด๋นํ๋ค.
๋ฎ์~์ค๊ฐ ์์ค์ ์ทจ์ฝ์ ์๋ 5๊ฐ ๋๊ตฌ ๋ชจ๋์์ ๋์ผํ์ง๋ง, ์น๋ช ์ ๋ฑ๊ธ์ ์ทจ์ฝ์ ์ ํด๋ก๋ ์ฝ๋(4๊ฑด), ๋ฐ๋น(1๊ฑด), ์ฝ๋ฑ์ค(1๊ฑด)์์ ์์ฑ๋๋ค.
๊ฐ์ฅ ์ฌ๊ฐํ ์ทจ์ฝ์ ์ API ์ธ๊ฐ ๋ก์ง๊ณผ ๋น์ฆ๋์ค ๋ก์ง์์ ๋ฐ๊ฒฌ๋๋ค. API ์ธ๊ฐ ๋ก์ง์ ๋๊ฐ ํน์ ๋ฆฌ์์ค์ ์ ๊ทผํ๊ฑฐ๋ ์ด๋ค ์์ ์ ์ํํ ์ ์๋์ง๋ฅผ ๊ฒ์ฆํ๋ ๊ธฐ๋ฅ์ด๋ฉฐ, ๋น์ฆ๋์ค ๋ก์ง์ ํ์ฉ๋ผ์๋ ์ ๋๋ ์ฌ์ฉ์ ํ์๋ฅผ ๊ตฌ๋ถํ๋ค. ๋ ์์ญ ๋ชจ๋ ์ ์์๊ฑฐ๋ ์์คํ ์์ ํต์ฌ์ ์ธ ๋ณด์ ์์๋ก ๊ผฝํ๋ค.
ํ ์์ด ์ฐ๊ตฌ์ง์ โAI๊ฐ ์์ฑํ ์ฝ๋ ์์ด์ ํธ๋ ๋น์ฆ๋์ค ๋ก์ง์ ํนํ ์ทจ์ฝํ ๊ฒฝํฅ์ด ์๋ค. ๊ฐ๋ฐ์๋ ์ํฌํ๋ก์ฐ๊ฐ ์ด๋ป๊ฒ ์๋ํด์ผ ํ๋์ง์ ๋ํ ์ง๊ด์ ์ดํด๋ฅผ ๋ฐํ์ผ๋ก ํ๋จํ์ง๋ง, ์์ด์ ํธ๋ ์ด๋ฌํ โ์์โ์ ๊ฐ์ถ์ง ๋ชปํด ๋๋ถ๋ถ ๋ช ์์ ์ธ ์ง์์ ์์กดํ๋คโ๋ผ๊ณ ์ค๋ช ํ๋ค.
๋ฐ๋ฉด ๊ธ์ ์ ์ธ ์ธก๋ฉด๋ ํ์ธ๋๋ค. ์ด๋ฒ ํ ์คํธ์์ ๋ฐ์ด๋ธ ์ฝ๋ฉ ๋๊ตฌ๋ SQL ์ธ์ ์ ์ด๋ ํฌ๋ก์ค์ฌ์ดํธ ์คํฌ๋ฆฝํ ๊ณผ ๊ฐ์ด, ์ค๋ซ๋์ ์ฌ๋์ด ์์ฑํ ์ ํ๋ฆฌ์ผ์ด์ ์ ๊ดด๋กญํ ์จ ๋ํ์ ์ธ ๋ณด์ ๊ฒฐํจ์ ๋น๊ต์ ์ ํํผํ๋ค. ์ด๋ค ์ทจ์ฝ์ ์ ์ฌ์ ํ OWASP ์น ์ ํ๋ฆฌ์ผ์ด์ ๋ณด์ ์ํ ์์ 10๋ ๋ชฉ๋ก์ ํฌํจ๋ผ ์๋ค.
ํ ์์ด๋ โ๊ฐ๋ฐํ ๋ชจ๋ ์ ํ๋ฆฌ์ผ์ด์ ์์ ์ ์ฉ ๊ฐ๋ฅํ SQL ์ธ์ ์ ์ด๋ XSS ์ทจ์ฝ์ ์ ํ ๊ฑด๋ ๋ฐ๊ฒฌ๋์ง ์์๋คโ๋ผ๊ณ ์ ํ๋ค.
ํํ ๋ฐ์ด๋ธ ์ฝ๋ฉ์ ์ผ์์ ์ธ ํ๋ก๊ทธ๋๋ฐ ์์ ์ ์๋ํํด ์์ฐ์ฑ์ ๋์ธ๋ค๋ ์ฅ์ ์ด ์์ฃผ ๊ฐ์กฐ๋๋ค. ์ด๋ ๋ถ๋ช ์ฌ์ค์ด์ง๋ง, ํ ์์ด์ ํ ์คํธ ๊ฒฐ๊ณผ๋ ์ด ๊ฐ์ ์ ๊ทผ์๋ ๋ถ๋ช ํ ํ๊ณ๊ฐ ์์์ ๋ณด์ฌ์ค๋ค. ์ฌ๋์ ๊ฐ๋ ๊ณผ ๋๋ฒ๊น ์ด ์ฌ์ ํ ํ์์ ์ด๋ผ๋ ๊ฒ์ด๋ค.
์ด๋ ์๋ก์ด ๋ฐ๊ฒฌ์ด ์๋๋ค. โ๋ฐ์ด๋ธ ์ฝ๋ฉโ์ด๋ผ๋ ๊ฐ๋ ์ด ๋ฑ์ฅํ ์ดํ ์ง๋ 1๋ ๋์, ์ ์ ํ ๊ฐ๋ ์ด ์๋ ๊ฒฝ์ฐ ๋๊ตฌ๊ฐ ์๋ก์ด ์ฌ์ด๋ฒ ๋ณด์ ์ทจ์ฝ์ ์ ์ ๋ฐํ ์ ์๋ค๋ ์ฐ๊ตฌ ๊ฒฐ๊ณผ๊ฐ ์ฌ๋ฌ ์ฐจ๋ก ์ ์๋ผ ์๋ค.
๋ฌธ์ ๋ ๋ฐ์ด๋ธ ์ฝ๋ฉ ํ๋ซํผ์ด ๋จ์ํ ์ฝ๋ ๋ด ๋ณด์ ๊ฒฐํจ์ ๋์น๋ค๋ ๋ฐ ๊ทธ์น์ง ์๋๋ค. ๊ฒฝ์ฐ์ ๋ฐ๋ผ์๋ ๋ฌด์์ด ์์ ํ๊ณ ๋ฌด์์ด ์ํํ์ง๋ฅผ ์ผ๋ฐ์ ์ธ ๊ท์น์ด๋ ์ฌ๋ก๋ก ์ ์ํ๋ ๊ฒ ์์ฒด๊ฐ ๋ถ๊ฐ๋ฅํ๋ค๋ ์ ์ด ๋ ํฐ ๊ณผ์ ๋ก ์ง์ ๋๋ค.
ํ ์์ด๋ ์๋ฒ ์ธก ์์ฒญ ์์กฐ(SSRF)๋ฅผ ์๋ก ๋ค๋ฉฐ, โ์ ์์ ์ธ URL ์์ฒญ๊ณผ ์ ์์ ์ธ ์์ฒญ์ ๊ตฌ๋ถํ๋ ๋ณดํธ์ ์ธ ๊ธฐ์ค์ ์กด์ฌํ์ง ์๋๋ค. ์์ ๊ณผ ์ํ์ ๊ฒฝ๊ณ๋ ๋งฅ๋ฝ์ ํฌ๊ฒ ์ข์ฐ๋๊ธฐ ๋๋ฌธ์ ์ ํํ๋ ํด๊ฒฐ์ฑ ์ ์ ์ฉํ๊ธฐ ์ด๋ ต๋คโ๋ผ๊ณ ์ค๋ช ํ๋ค.
์ด์ ๋ฐ๋ผ ์ ๊ณ์์๋ ๋ฐ์ด๋ธ ์ฝ๋ฉ ์์ด์ ํธ๋ฟ๋ง ์๋๋ผ, ์ด๋ฅผ ๊ฒ์ฆํ๊ณ ์ ๊ฒํ๋ ๋ฐ์ด๋ธ ์ฝ๋ฉ ๊ฒ์ฌ ์์ด์ ํธ์๋ ์ฃผ๋ชฉํด์ผ ํ๋ค๋ ์ง์ ์ด ๋์จ๋ค. ์๊ท๋ชจ ์คํํธ์ ์ธ ํ ์์ด๋, ๋ฐ์ด๋ธ ์ฝ๋ฉ์ ๊ฒ์ฆํ๋ ๊ธฐ์ ์์ญ์์ ํ์ฌ๋ก์๋ ๋๋ ทํ ํด๋ฒ์ด ์ ์๋์ง ์๊ณ ์๋ค๊ณ ๋ณด๊ณ ์๋ค. ํ ์์ด๋ โํ ์คํธ์ ์ต๊ทผ ์ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ์ข ํฉํ๋ฉด ์ด ๋ฌธ์ ๋ฅผ ํฌ๊ด์ ์ผ๋ก ํด๊ฒฐํ ์ ์๋ ์๋ฃจ์ ์ ์์ง ์กด์ฌํ์ง ์๋๋ค. ๊ฐ๋ฐ์๊ฐ ์ฝ๋ฉ ์์ด์ ํธ์ ์ผ๋ฐ์ ์ธ ํจ์ ์ ์ดํดํ๊ณ ์ด์ ๋๋นํ๋ ๊ฒ์ด ์ค์ํ๋คโ๋ผ๊ณ ์ธ๊ธํ๋ค.
๋ฐ์ด๋ธ ์ฝ๋ฉ๊ณผ ๊ด๋ จํ ๋ณด๋ค ๊ทผ๋ณธ์ ์ธ ์ง๋ฌธ์ ๋๊ตฌ์ ์ฑ๋ฅ์ด ์๋๋ผ ์ฌ์ฉ ๋ฐฉ์์ด๋ค. ๊ฐ๋ฐ์์๊ฒ ๊ฒฐ๊ณผ๋ฌผ์ ๊ผผ๊ผผํ ํ์ธํ๋ผ๊ณ ๋งํ๋ ๊ฒ๊ณผ, ์ค์ ๋ก ๊ทธ๋ฐ ๊ฒํ ๊ฐ ํญ์ ์ด๋ค์ง๋ค๊ณ ์ ์ ํ๋ ๊ฒ์ ๋ค๋ฅธ ๋ฌธ์ ๋ค. ์ฌ๋์ด ์ง์ ์ฝ๋๋ฅผ ์์ฑํ๋ ์๊ธฐ์๋ ๋ชจ๋ ์ค์๊ฐ ์ฌ์ ์ ํต์ ๋์ง๋ ์์๋ค.
๋ณด์ ์๋น์ค ๊ธฐ์ ํ๋ฆฌ์จ(Talion)์ ๊ณต๊ฒฉ ๋ณด์ ์ด๊ด์ธ ๋งคํ ๋ก๋น์ค๋ โ๋ฐ์ด๋ธ ์ฝ๋ฉ ๋ฐฉ์์ ๋์ ํ ๋ ๊ธฐ์ ์ ๋ณด์ ์ฝ๋ ๊ฒํ ๊ฐ ์ ์ฒด ๋ณด์ ์ํํธ์จ์ด ๊ฐ๋ฐ ์ฃผ๊ธฐ์ ์ผ๋ถ๋ก ํฌํจ๋๊ณ ์ง์์ ์ผ๋ก ์คํ๋๋๋ก ํด์ผ ํ๋ค. OWASP ์์ ํ ์ฝ๋ฉ ๊ดํ์ด๋, SEI CERT ์ฝ๋ฉ ํ์ค๊ณผ ๊ฐ์ ์ธ์ด๋ณ ํ๋ ์์ํฌ ๋ฑ ๊ฒ์ฆ๋ ๋ชจ๋ฒ ์ฌ๋ก๋ ํจ๊ป ํ์ฉํด์ผ ํ๋คโ๋ผ๊ณ ์ค๋ช ํ๋ค.
๋ก๋น์ค๋ ์ฝ๋๊ฐ ๋ฐฐํฌ๋๊ธฐ ์ ์ ์ ๋ถ์๊ณผ ๋์ ๋ถ์์ ํตํด ๋ฐ๋์ ๊ฒ์ฆํด์ผ ํ๋ค๊ณ ๋ง๋ถ์๋ค. ๊ด๊ฑด์ ๋๋ฒ๊น ์ ์ด๋ป๊ฒ ์ ๋๋ก ์ํํ๋๋๋ค. ๊ทธ๋ โ๋ฐ์ด๋ธ ์ฝ๋ฉ์ ๋ถ๋ช ์ํ์ ์๋ฐํ์ง๋ง, ์ ํต์ ์ธ ๋๋ฒ๊น ๊ณผ ํ์ง ๋ณด์ฆ์ ๋์ด์๋ ์ ๊ณ ํ์ค ํ๋ก์ธ์ค์ ๊ฐ์ด๋๋ผ์ธ์ ์ถฉ์คํ ๋ฐ๋ฅด๋ฉด ๊ด๋ฆฌ ๊ฐ๋ฅํ ์์คโ์ด๋ผ๊ณ ๋ถ์ํ๋ค.
๋ฐ๋ฉด ์ ํ๋ฆฌ์ผ์ด์ ํ ์คํธ ๊ธฐ์ ์ฒดํฌ๋งํฌ์ค(Checkmarx)์ ์ ํ ๋ง์ผํ ๋ถ์ฌ์ฅ ์๋ ํจ์ค๋ธ๋ฃจ๋๋ ์ ํต์ ์ธ ๋๋ฒ๊น ๋ฐฉ์์ด AI ์๋์๋ ํ๊ณ์ ์ง๋ฉดํ ์ ์๋ค๊ณ ์ง์ ํ๋ค.
ํจ์ค๋ธ๋ฃจ๋๋ โAI ์๋๋ก ์งํ๋๋ ๋ฌธ์ ์ ๋ํด ๋ ๋ง์ ๋๋ฒ๊น ์ ์๊ตฌํ๋ ์๋ชป๋ ๋์โ์ด๋ผ๋ฉฐ โ๋๋ฒ๊น ์ AI๊ฐ ์์ฑํ ์ฝ๋๋ฅผ ์ฌํ์ ์ฌ๋์ด ์ถฉ๋ถํ ๊ฒํ ํ ์ ์๋ค๋ ์ ์ ๋ฅผ ๊น๊ณ ์์ง๋ง, ๋ฐ์ด๋ธ ์ฝ๋ฉ์ ๊ท๋ชจ์ ์๋์์๋ ๊ทธ๋ฐ ์ ์ ๊ฐ ๋ ์ด์ ์ฑ๋ฆฝํ์ง ์๋๋คโ๋ผ๊ณ ๋งํ๋ค.
๊ทธ๋ ์ด์ด โํ์ค์ ์ธ ํด๋ฒ์ ๋ณด์์ ๊ฐ๋ฐ ์ดํ๊ฐ ์๋๋ผ ์ฝ๋ ์์ฑ ๋จ๊ณ์ ํฌํจ์ํค๋ ๊ฒโ์ด๋ผ๋ฉฐ โAI ์ฝ๋ฉ ์ด์์คํดํธ์ ํจ๊ป ์๋ํ๋ ์์ด์ ํธ ๊ธฐ๋ฐ ๋ณด์์ด ๊ฐ๋ฐ ํ๊ฒฝ ์์ ๊ธฐ๋ณธ์ ์ผ๋ก ํตํฉ๋ผ์ผ ํ๋คโ๊ณ ์ค๋ช
ํ๋ค.
dl-ciokorea@foundryco.com
Welcome back, aspiring cyberwarriors!
If youโve ever conducted an OSINT investigation, you probably know that the dark web is one of the hardest places to investigate. Whether youโre tracking ransomware groups or looking for leaked passwords manually searching through dark web results takes hours and gives you mostly junk and malware. This is where AI can change how you investigate. By using Large Language Models we can improve our searches and filter results faster. To do this, we have a tool called Robin.
In this article, weโll explore how to install this tool, how to use it, and what features it provides. Letโs get rolling!
Robin is an open-source tool for investigating the dark web. It uses AI to improve your searches, filter results from dark web search engines, and summarize what you find. What makes Robin particularly valuable is its multi-model support. You can easily switch between OpenAI, Claude, Gemini, or local models like Ollama depending on your needs, budget, and privacy requirements. The tool is CLI-first, built for terminal users who want to integrate dark web intelligence into their existing workflows.
For this demonstration, Iโll be using a Raspberry Pi as the hacking platform, but you can easily replicate all the steps using Kali or any other Debian-based distribution. To install the tool, we can either use the source code from GitHub or Docker. I will choose the first option. To begin, clone the repository first:
pi> git clone https://github.com/apurvsinghgautam/robin.git
As shown in the downloaded files, this is a Python project. We need to create a virtual environment and install the required packages.
pi> python -m venv venv
pi> source venv/bin/activate
pi> pip3 install -r requirements.txt
Before Robin can search the dark web, we need to have Tor running on your system. Install Tor by opening your terminal and executing the following command:
pi> sudo apt install tor
In this demonstration, I will be using Googleโs Gemini models. You can easily create an API key in Google AI Studio to access the models. If you open the config.py file, you will see which models support the tool.
Robin can be configured using either a .env file or system environment variables. For most users, creating a .env file in your Robin directory provides the cleanest approach. This method keeps your API credentials organized and makes it easy to switch between different configurations. Open the file in your preferred text editor and add your Gemini API key.
First, letโs open the help screen to see which options this tool supports and to verify that we installed it correctly.
pi> python3 main.py โhelp
Currently, we can see two supported modes for using this tool: CLI and web UI. I prefer CLI, so I will demonstrate that. Letโs explore the help screen of the CLI mode.
pi> python3 main.py cli โhelp
Itโs a straightforward help screen; we simply need to specify an LLM model and our query. Letโs search for credential exposure.
pi> python3 main.py cli -m gemini-2.5-flash -q โsensitive credentials exposureโ
After a few minutes of processing, Robin produced the gathered information on the terminal. By default, it is formatted in Markdown and saved to a file with a name based on the current date and time. To view the results with Markdown formatting, Iโll use a command-line tool called glow.
pi> glow summary-xx-xx.md
The analysis examined various Tor-based marketplaces, vendors, and leak sources that advertise stolen databases and credentials. The findings reveal a widespread exposure of personally identifiable information (PII), protected health information (PHI), financial data, account credentials, and cryptocurrency private keys associated with major global organizations and millions of individuals. The report documents active threat actors, their tactics, and methods of monetization. Key risks have been identified, along with recommended next steps.
While Robin is a powerful tool for dark web OSINT, itโs important to understand its limits. The tool uses dark web search engines, which only index a small part of whatโs actually on hidden services. Many dark websites block indexing or require you to log in, so Robin canโt reach them through automated searches. For thorough investigations, youโll still need to add manual research and other OSINT methods to what Robin finds.
The quality of Robinโs intelligence summaries depends a lot on the LLM youโre using and the quality of what it finds. Gemini 2.5 Flash gives great results for most investigations, but the AI can only work with the information in the search results. If your search doesnโt match indexed content, or if the information you need is behind a login wall, Robin wonโt find it.
Conducting investigations on the dark web can be time-consuming when using traditional search tools. Since the dark web relies on anonymity networks, isnโt indexed by standard search engines, and contains a vast amount of irrelevant information, manual searching can often be slow and ineffective. Robin addresses these challenges by leveraging AI to enhance your searches, intelligently filter results, and transform findings into useful intelligence reports. While this tool does have limitations, it can be a valuable addition to your arsenal when combined with manual searching and other OSINT tools.
If youโre interested in deepening your knowledge of OSINT investigations or even starting your own investigation business, consider exploring our OSINT training to enhance your skills.
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