Google introduced Gemini 3.8 Flash Cyber, a cybersecurity-tuned model with more permissive cyber mitigations, available only to trusted defenders through a new Fairwind Program. Google says it prioritized vulnerability fixing over exploitation and reports 47.2% pass@1 on Collinear's CWE-Bench patching benchmark, over 70% on an internal 20-language discovery benchmark, and 2.6 times more correct Chrome patches than larger commercial models.
Why it matters
It is a gated, defense-oriented model release that foregrounds patching metrics rather than offensive capability.
Key facts
As stated in the sources, with where to find them.
- CWE-Bench (run by Collinear): 3.8 Flash Cyber pass@1 47.2% vs 47.8% for an unnamed leading frontier model, at lower cost.Section 'Automated patching'
- Internal benchmark across 20 programming languages: success rate exceeding 70%.Section 'Autonomous vulnerability discovery'
- Chrome Security found it produced 2.6x more correct patches than the best larger commercial models; Wiz reports +7.5-9.7% recall at 2.3-5.2x lower cost on its internal pentest benchmark.Section 'Real-world impact'
- Available only to trusted defenders via the Fairwind Program; ships with more permissive cybersecurity mitigations.Sections on availability and safety
Findings that cite this record
No tracked finding cites this record yet.
Key questions this bears on
- How far can measured AI cyber capability be trusted?As a lower or conditional bound. Scores move substantially with token budget, evaluation pipeline, and benchmark contamination.
- Is AI shifting the balance between finding and fixing vulnerabilities?Discovery is ahead. AI finds real vulnerabilities faster than they are fixed, and simple checks overstate how often AI patches work.
- How are attackers using AI agents in real operations?Increasingly to run parts of intrusions: providers and vendors report agent-driven espionage, extortion and credential theft, and malware that queries LLMs.
Sources
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