Real-world vulnerability discovery
Agents search popular open-source codebases to rediscover about 1,200 recent confirmed vulnerabilities across many languages. Reports share discovered.
In-house Google DeepMind evaluation. The tasks are not public.
- Level
- Expert Specialists with years of training, often over hours of work
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Agent task Many steps in a terminal, browser, desktop, app, game or robot.
Gemini 4 Argon leads with 86%
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 86% | Oct 2026 | Model card | |
| 2 | | 71% | Sep 2026 | Model card |
The best score passed 85% in Oct 2026
All the scores we have, one dot each, so a model tested at several settings appears more than once.
One lab put it in a launch post in the last six months
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| 2 Sep 2026 | 71 | Real-world vulnerability discovery, internal benchmark across 20 languages |
One system card reports it
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| 13 Oct 2026 | | 86 | Real-world vulnerability discovery (internal), historical vulnerabilities discovered 86% (7.1.2) | Cyber risk |
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Gemini 3.5 Flash Cyber 72%