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Open Source Archive

The AI Cyber Challenge was designed to advance cybersecurity technology AND ensure that technology is applied to secure the code we all rely on. To that end, all 7 finalist teams are releasing their competition Cyber Reasoning Systems (CRSs) open-source in order to accelerate the distribution and use of the AIxCC-developed technology within the cybersecurity and software development fields.

In addition, you are invited to access, test, use and build on the following:

→ AIxCC competition infrastructure

→ Competition Challenges

→ Cyber Reasoning Unified Model Benchmark System (CRUMBS)

→ Competition harness documentation

→ And more!

https://archive.aicyberchallenge.com/

42 Beyond Bug
https://b3yond.org/

Atlanta won the competition the group’s name is 42 Beyond Bug
The have an open archive of the tools/source code for the tools.
https://github.com/42-b3yond-6ug/42-b3yond-6ug-crs

Title: OpenAI’s New Aardvark GPT-5 Agent that Detects and Fixes Vulnerabilities Automatically

Source: Cyber Security News

Date Published: November 2, 2025

Excerpt:

"Aardvark functions through a sophisticated multi-stage pipeline that mimics the investigative process of a seasoned security researcher.

It begins with a comprehensive analysis of an entire repository to generate a threat model, capturing the project’s security objectives and potential risks.

Next, during commit scanning, the agent examines code changes against this model, identifying vulnerabilities in real-time as developers push updates; for initial integrations, it reviews historical commits to uncover latent issues.

...

Explanations are provided step-by-step, with annotated code snippets for easy human review, ensuring transparency.​

Following detection, validation occurs in a sandboxed environment where Aardvark attempts to exploit the flaw, confirming its real-world impact and minimizing false positives.

This isolated testing describes the exact steps taken, delivering high-fidelity insights. For remediation, Aardvark leverages OpenAI’s Codex to generate precise patches, attaching them directly to findings for one-click application after review.

Unlike traditional methods such as fuzzing or static analysis, Aardvark employs LLM-powered reasoning to comprehend code behavior deeply, also spotting non-security bugs like logic errors.

The process integrates seamlessly with GitHub and other tools, maintaining development velocity.​"

To read the complete article see:

https://cybersecuritynews.com/aardvark-gpt-5-agent/