๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค (@z0idsec) header
๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค (@z0idsec) profile picture

Content Engineer at PentesterLab Creator of Attaxr Building cybersecurity tools and SaaS Opinions are my own and do not represent my employer.

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Joined September 2018
Photo by ๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค (@z0idsec)Photo by ๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค (@z0idsec)Photo by ๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค (@z0idsec)Photo by ๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค (@z0idsec)Photo by ๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค (@z0idsec)Photo by ๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค (@z0idsec)Photo by ๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค (@z0idsec)Photo by ๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค (@z0idsec)Photo by ๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค (@z0idsec)Photo by ๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค (@z0idsec)
AI agents don't always follow the right design patterns. I built this product to help agents use established design patterns via MCP, helping keep codebases clean and maintainable. It's a tool, not a magic fix. Always review your code. Check it out: aipatterns.dev/agents
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I Built a local bug bounty recon platform that runs in the background: Rust tools handle subdomains, DNS, probing and crawling, a local systemone model classifies assets and flags leads. Argus MCP lets a hackbot poll for leads, pull them and hunt for bugs while I test in Burp.
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Very useful information ๐Ÿง  the quirky behaviour in programming languages can lead to interesting bypasses.
Same trap, two languages: Python: os.path.join("/app", "/foo/bar") is "/foo/bar" C#: Path.Combine("/app", "/foo/bar") is "/foo/bar" In the happy path they do what you expect, so people never look further.
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We built security tools to automate tasks with predefined rules, but they struggled with edge cases. Harnesses add reasoning, letting tools interpret results and adapt, with HITL keeping humans in control.
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Without a good harness, you're just finding the same shit as everyone else: the new era of Nuclei. A well-engineered harness is like giving your lab rat tren (Nuclei private templates). But finding the right balance between manual hacking and your hackbot? activates god mode.
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I'm curious on how well it works for y'all vibe coders, would love some of your amazing feedback. Remember, it's not a magic fix, your agents will always have a mind of it's own at times, so make sure to validate there responses and review the code it spits out.
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Definitely worth a read ๐Ÿ”ฅ you won't regret it and you will learn lots. Great work Louis ๐Ÿ’ช
If you've read my book The CVE Archeologist's Field Guide, an honest Amazon review would really help. Any rating. One or two sentences is plenty: what was useful, what was missing. It has 5 ratings so far, and for a niche book that's the first thing strangers check.
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This is amazing ๐Ÿ‘ the profundis team has completely refurbished there UI/UX and they always have clean data and some of the best features I've seen to date. It's one of the best Shodan alternatives, I would highly recommend giving them a try out. #bugbounty #recon #profundis
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Great work Harley! you're posting some great content for the community ๐Ÿ’ชkeep up the epic work.
Replying to @HacktronAI
@HacktronAI names a July intrusion chain into @OpenAI , @MetaBugBounty announces a public Muse bounty up to $300K, @efaav finds unsigned JWT auth in a Microsoft analytics API tied to 17 trillion records, and more. This week, Disclosed. #BugBounty Full issue โ†’ getdisclosed.com Highlights below ๐Ÿ‘‡ @MetaBugBounty takes its Muse AI-agent bounty public, up to $300K for qualifying vulns and high-impact prompt injection. @HacktronAI documents a chained intrusion into @OpenAI, starting from an image parsing bug and ending in RCE plus downstream identity and SSO abuse. @efaav walks through unsigned JWTs in an internal Microsoft analytics API, claim spoofing unlocked arbitrary queries, the write-up frames the blast radius as 17 trillion records. @vercel consolidates private and OSS coverage into one public @Hacker0x01 program spanning Vercel products and open-source projects. @Intigriti confirms @Adobeโ€™s public bug bounty program migration, going live on September 1, 2026. @AnthropicAI announces a public @Hacker0x01 bug bounty after running privately with invited researchers. Anthropicโ€™s September 2026 threat report summarizes observed Claude misuse, including multi-agent phishing and AI-augmented cyber workflows. @NahamSec announces NahamCon โ€œPrompt2Pwn,โ€ a live hacking event format for 2026. @forefy releases reburp, a Burp extension that exposes the Montoya API as a localhost OpenAPI REST interface for external scripts and agents. @Pillar_sec reports session spoofing and SSRF in Grafana MCP, one issue enabled unauthenticated tool execution with server-side privileges. @0xacb drops a GeoNetwork pre-auth RCE chain write-up, unauth formatter upload plus unsafe XSLT reached code execution. @SLCyberSec details Goja JavaScript engine exploitation, out-of-bounds heap write to arbitrary read/write and full RCE. @devploit ships geminiHunter, scanning web assets and Android apps for exposed Google Gemini API keys, plus validation checks. @Antisy_Training publishes โ€œExfil Everything,โ€ a survey of real-world data theft chains against AI agents and their trust boundaries. That's not all. Full links, writeups & more โ†’ getdisclosed.com Bug bounty and offensive AI, curated.
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๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค retweeted
Why is AI code review so easy to adopt? What makes pentesting agents harder to deploy? Which skills should you keep developing? Watch the recording of our webinar: "The Uneven Impact of AI on Offensive Security" with @PentesterLab's founder @snyff: youtube.com/watch?v=IqghiUqxโ€ฆ
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Check out PentesterLabs YT channel, there is some great content for everyone. @snyff has been working very hard ๐Ÿ’ช๐Ÿ”ฅ
๐Ÿซถ๐Ÿซถ๐Ÿซถ "Like and Subscribe" ๐Ÿซถ๐Ÿซถ๐Ÿซถ
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One of the biggest mistakes beginners make when testing an application is not reading the error messages properly. They send a payload, get an error and conclude that it did not work. Then they send another payload, get another error and assume it is basically the same thing. But an error does not mean the payload did not work. It just means that an error was triggered somewhere in the execution path, and that point may be after the interesting part already happened. Your payload may have been parsed successfully, changed the control flow, bypassed a check, reached a different function or triggered behaviour that the previous payload did not. Something later may simply have failed. This is why small differences matter so much. A different exception, a slightly different message, a different status code or even a different location in a stack trace can tell you that you moved forward. Security testing is often about noticing those tiny changes and asking why they happened. Donโ€™t just look for success or failure. Read the error.
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Small improvements day by day, fingers crossed having an extra pair of eyes can help my team find some interesting leads to hack on ๐Ÿค˜
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Been building an event-driven AI recon classifier for me and the team. One thing I've learned: test your harness constantly and keep tweaking your skills + system prompts. Models already know the common stuff. Build skills around the things they don't.
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Very interesting ๐Ÿ‘Œ
I have spent a fair amount of time writing SQL (Injections), and today I learnt that LIKE has an ESCAPE clause that lets you redefine the escape character! > SELECT 'PTL%' LIKE 'PTLX%'; -- 0 > SELECT 'PTL%' LIKE 'PTLX%' ESCAPE 'X'; -- 1
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You canโ€™t demo or benchmark your AI pentester against Juice Shop and expect to be taken seriously.
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๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค retweeted
Claude can hunt. Now it can see. The Profundis MCP gives Claude the one thing it was missing in bug bounty: recon data. Hosts, DNS, WHOIS, TLS certs, subdomains, ASN, perceptual favicon search. Watch it map a real public target end-to-end.
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The team at profundis have really been at work improving there platform. You should all go and check out there favicon similarity search that allows you to find hosts that are alike based on favicon differences, I've used it and it's brilliant definitely my favourite.
๐Ÿšจ Profundis update ๐Ÿšจ Over the last few weeks Profundis changed a lot - for the better. A new credit system, 100M+ new similar favicons, grouped results, and our powerful recon engine is now quietly backfilling bug-bounty scopes. Thread ๐Ÿงต
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๐˜ป๐˜ฐ๐˜ช๐˜ฅ๐˜ด๐˜ฆ๐˜ค retweeted
๐—ฅ๐—ฒ๐˜€๐—ฒ๐—ฎ๐—ฟ๐—ฐ๐—ต ๐—ช๐—ผ๐—ฟ๐˜๐—ต ๐—ฅ๐—ฒ๐—ฎ๐—ฑ๐—ถ๐—ป๐—ด - ๐—ช๐—ฒ๐—ฒ๐—ธ ๐Ÿญ๐Ÿด, ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ The consensus seems to be: models don't matter... ๐Ÿค– ๐—”๐—œ ๐˜๐—ต๐—ฟ๐—ฒ๐—ฎ๐˜๐˜€ ๐—ถ๐—ป ๐˜๐—ต๐—ฒ ๐˜„๐—ถ๐—น๐—ฑ: ๐—ง๐—ต๐—ฒ ๐—ฐ๐˜‚๐—ฟ๐—ฟ๐—ฒ๐—ป๐˜ ๐˜€๐˜๐—ฎ๐˜๐—ฒ ๐—ผ๐—ณ ๐—ฝ๐—ฟ๐—ผ๐—บ๐—ฝ๐˜ ๐—ถ๐—ป๐—ท๐—ฒ๐—ฐ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—ผ๐—ป ๐˜๐—ต๐—ฒ ๐˜„๐—ฒ๐—ฏ A quick list of indirect prompt injection examples Google came across: security.googleblog.com/2026โ€ฆ. ๐ŸชŸ ๐—ฃ๐—ฒ๐—ฟ๐˜€๐—ถ๐˜€๐˜๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—”๐˜๐—น๐—ฎ๐˜€: ๐Ÿญ๐Ÿต ๐—ง๐—ฒ๐—ฐ๐—ต๐—ป๐—ถ๐—พ๐˜‚๐—ฒ๐˜€ ๐—ก๐—ผ๐—ฏ๐—ผ๐—ฑ๐˜† ๐—ง๐—ฎ๐—น๐—ธ๐˜€ ๐—”๐—ฏ๐—ผ๐˜‚๐˜ A great list of persistence methods for AD and Windows: 0xsr.com/blog/windows-persisโ€ฆ. ๐Ÿ˜ณ ๐—ฆ๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐—ป๐—ด ๐—š๐—ถ๐˜๐—›๐˜‚๐—ฏ: ๐—ช๐—ถ๐˜‡ ๐—ฅ๐—ฒ๐˜€๐—ฒ๐—ฎ๐—ฟ๐—ฐ๐—ต ๐˜‚๐—ป๐—ฐ๐—ผ๐˜ƒ๐—ฒ๐—ฟ๐˜€ ๐—ฅ๐—–๐—˜ ๐—ถ๐—ป ๐—š๐—ถ๐˜๐—›๐˜‚๐—ฏ.๐—ฐ๐—ผ๐—บ RCE on github.com using a single git push.: wiz.io/blog/github-rce-vulneโ€ฆ. ๐Ÿค– ๐—™๐—ถ๐—ป๐—ฑ๐—ถ๐—ป๐—ด ๐—ญ๐—ฒ๐—ฟ๐—ผ-๐——๐—ฎ๐˜†๐˜€ ๐˜„๐—ถ๐˜๐—ต ๐—”๐—ป๐˜† ๐— ๐—ผ๐—ฑ๐—ฒ๐—น Niels Provos leveraging IronCurtain (and its vuln-discovery workflow) to find vulnerabilities: provos.org/p/finding-zero-daโ€ฆ. ๐Ÿค– ๐—ช๐—ต๐˜† ๐— ๐˜†๐˜๐—ต๐—ผ๐˜€ ๐—ฑ๐—ผ๐—ฒ๐˜€๐—ป'๐˜ ๐—บ๐—ฎ๐˜๐˜๐—ฒ๐—ฟ (๐—ณ๐—ผ๐—ฟ ๐˜‚๐˜€) A great write-up from liveoverflow on why small models may be a better solution: hacktron.ai/blog/why-mythos-โ€ฆ. โ– ๐—›๐—”๐—ฃ๐—ฟ๐—ผ๐˜…๐˜† ๐—›๐—ง๐—ง๐—ฃ/๐Ÿฏ -> ๐—›๐—ง๐—ง๐—ฃ/๐Ÿญ ๐——๐—ฒ๐˜€๐˜†๐—ป๐—ฐ: ๐—–๐—ฟ๐—ผ๐˜€๐˜€-๐—ฃ๐—ฟ๐—ผ๐˜๐—ผ๐—ฐ๐—ผ๐—น ๐—ฆ๐—บ๐˜‚๐—ด๐—ด๐—น๐—ถ๐—ป๐—ด ๐˜ƒ๐—ถ๐—ฎ ๐—ฎ ๐—ฆ๐˜๐—ฎ๐—ป๐—ฑ๐—ฎ๐—น๐—ผ๐—ป๐—ฒ ๐—ค๐—จ๐—œ๐—– ๐—™๐—œ๐—ก (๐—–๐—ฉ๐—˜-๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ-๐Ÿฏ๐Ÿฏ๐Ÿฑ๐Ÿฑ๐Ÿฑ) It's rare to see this level of details in a blog post. Too Long, Must Read: r3verii.github.io/cve/2026/0โ€ฆ.
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This is a solid video to learn common system architecture problems and how to solve them: ๐Ÿ‘‰ youtube.com/watch?v=s9Qh9fWeโ€ฆ Good knowledge to have as a hacker so you understand how systems work and how to spot weaknesses.
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