Agentic data science with the Data Agent Kit
cloud.google.com·7h ago
Data Science
Simon Willison's Blog·13d ago·5 min read
Quoting Anthropic Frontier Red Team
TL;DR
GLM-5.3 and Claude Mythos Preview were evaluated on 100 tasks, revealing that GLM-5.3 achieved control flow hijacks in 4% of trials, while Claude Mythos Preview succeeded in 6%. This marks a significant advancement over earlier models, which failed to achieve any hijacks.
✦ Why It Matters
Evaluate your current AI models against advanced benchmarks to ensure they are secure from exploitation.
Key Takeaways
- Assess your AI models against the latest benchmarks.
- Monitor advancements in AI capabilities related to cybersecurity.
- Consider the implications of AI model performance on security.
- Stay informed about emerging threats from advanced AI models.
Full Summary
In a recent evaluation, GLM-5.3 and Claude Mythos Preview were tested against 100 randomly selected tasks from an internal Binary Exploitation benchmark, which assesses the ability of models to exploit software vulnerabilities. GLM-5.3 demonstrated control flow hijacks in 4% of trials, while Claude Mythos Preview outperformed it with a 6% success rate.
Notably, earlier models like Claude Opus 4.6 and GLM-5.2 did not succeed in any of the tasks, indicating a significant leap in capability. This evaluation highlights the growing sophistication of AI models in cybersecurity contexts, particularly in executing complex exploits.
The results suggest that as models evolve, they may increasingly pose risks in terms of security vulnerabilities.