Getting Started with Exploit Development

Cybersecurity Notes

Welcome to my blog! There's a lot here and it's a bit spread out, so here's a guide:

Today's PHP Security Release, and How We're Strengthening PHP Security

Describing the story behind how critical security vulnerabilities were found and fixed.

Today's PHP Security Release, and How We're Strengthening PHP Security

Describing the story behind how critical security vulnerabilities were found and fixed.

The-Art-of-Hacking/h4cker

This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security, vulnerability research, exploit development, reverse engineering, and more. 🔥 Also check: https://hackertraining.org

SagarBiswas-MultiHAT/awesome-cybersecurity-books

A curated collection of 70+ free cybersecurity books organized by domain and difficulty (🟢 Beginner → 🟡 Intermediate → 🔴 Advanced). Structured learning paths for ethical hacking, penetration testing, exploit development, malware analysis, web security, and more. No paywall. Community maintained.

ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks?

AI agents are rapidly gaining capabilities that could significantly reshape cybersecurity, making rigorous evaluation urgent. A critical capability is exploitation: turning a vulnerability, which is not yet an attack, into a concrete security impact, such as unauthorized file access or code execution. Exploitation is a particularly challenging task because it requires low-level program reasoning (e.g., about memory layout), runtime adaptation, and sustained progress over long horizons. Meanwhile, it is inherently dual-use, supporting defensive workflows while lowering the barrier for offense. Despite its importance and diagnostic value, exploitation remains under-evaluated. To address this gap, we introduce ExploitGym, a large-scale, diverse, realistic benchmark on the exploitation capabilities of AI agents. Given a program input that triggers a vulnerability, ExploitGym tasks agents with progressively extending it into a working exploit. The benchmark comprises 898 instances sourced from real-world vulnerabilities across three domains, including userspace programs, Google's V8 JavaScript engine, and the Linux kernel. We vary the security protections applied to each instance, isolating their impact on agent performance. All configurations are packaged in reproducible containerized environments. Our evaluation shows that while exploitation remains challenging, frontier models can successfully exploit a non-trivial fraction of vulnerabilities. For example, the strongest configurations are Anthropic's latest model Claude Mythos Preview and OpenAI's GPT-5.5, which produce working exploits for 157 and 120 instances, respectively. Notably, even with widely used defenses enabled, models retain non-trivial success rates. These results establish ExploitGym as an effective testbed for exploitation and highlight the growing cybersecurity risks posed by increasingly capable AI agents.

ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks?

AI agents are rapidly gaining capabilities that could significantly reshape cybersecurity, making rigorous evaluation urgent. A critical capability is exploitation: turning a vulnerability, which is not yet an attack, into a concrete security impact, such as unauthorized file access or code execution. Exploitation is a particularly challenging task because it requires low-level program reasoning (e.g., about memory layout), runtime adaptation, and sustained progress over long horizons. Meanwhile, it is inherently dual-use, supporting defensive workflows while lowering the barrier for offense. Despite its importance and diagnostic value, exploitation remains under-evaluated. To address this gap, we introduce ExploitGym, a large-scale, diverse, realistic benchmark on the exploitation capabilities of AI agents. Given a program input that triggers a vulnerability, ExploitGym tasks agents with progressively extending it into a working exploit. The benchmark comprises 898 instances sourced from real-world vulnerabilities across three domains, including userspace programs, Google's V8 JavaScript engine, and the Linux kernel. We vary the security protections applied to each instance, isolating their impact on agent performance. All configurations are packaged in reproducible containerized environments. Our evaluation shows that while exploitation remains challenging, frontier models can successfully exploit a non-trivial fraction of vulnerabilities. For example, the strongest configurations are Anthropic's latest model Claude Mythos Preview and OpenAI's GPT-5.5, which produce working exploits for 157 and 120 instances, respectively. Notably, even with widely used defenses enabled, models retain non-trivial success rates. These results establish ExploitGym as an effective testbed for exploitation and highlight the growing cybersecurity risks posed by increasingly capable AI agents.

Hack-with-Github/Awesome-Hacking

A collection of various awesome lists for hackers, pentesters and security researchers

CLI quickstart – Codex Security | ChatGPT Learn

Set up Codex Security, run a local scan, and review the report, findings, and coverage.

Hacker, Hack Thyself

We’ve read so many sad stories about communities that were fatally compromised or destroyed due to security exploits. We took that lesson to heart when we founded the Discourse project; we endeavor to build open source software that is secure and safe for communities by default, even if there

Just a rumour of a bug is enough to find a security exploit these days

Thinking through how the conventional OSS security embargoes no longer buy us time, and what open source maintainers might do instead to respond

Using Claude to reduce the attack surface of code

Automated attack surface analysis and reduction can meaningfully improve the security of deployed software in the near term. In this post, we preview data we’ve collected from applying attack surface reduction techniques to large open-source codebases using Claude.

Announcing Magika 1.0: now faster, smarter, and rebuilt in Rust

Elie Bursztein, Julien Cretin, and Yanick Fratantonio, Applied Cybersecurity Research