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anthropic ai-safety public-models vulnerability-research

We reproduced Anthropic's Mythos findings with public models

blog.vidocsecurity.com

April 17, 2026

16 min read

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51/100

Summary

Anthropic's Mythos and Project Glasswing suggest that advanced AI vulnerability research should be restricted, but replication studies show that similar capabilities are already present in public models. Frontier models are increasingly effective at identifying serious vulnerabilities in real software.

Key Takeaways

Public AI models, such as GPT-5.4 and Claude Opus 4.6, can reproduce significant findings from Anthropic's Mythos, indicating that advanced AI vulnerability research is not limited to proprietary models.
The replication results showed that while public models successfully replicated vulnerabilities in FreeBSD and Botan, they had mixed results with FFmpeg and wolfSSL.
The methodology used in the vulnerability research involves a systematic process of inspection, validation, and prioritization, rather than a single prompt or output.
The shift in AI-assisted vulnerability research suggests that the focus is moving from model access to the challenges of validating and operationalizing findings in real-world applications.

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Community Sentiment

Mixed

Positives

The discussion highlights the importance of reproducibility in AI research, emphasizing that clear experimental setups are crucial for validating model claims.
The ability of Mythos to identify vulnerabilities without overly specific prompts suggests a significant advancement in AI's application to security tasks.

Concerns

Critics argue that the reproduction attempts lack transparency regarding the exact prompts used by Anthropic, raising concerns about the validity of the findings.
There is skepticism about the claims made by Mythos, with some suggesting that the real advancements may stem from the harness rather than the model itself.