SEC-Bench ProBrowse 284 families
SEC-Bench Pro
Can the model diagnose or complete difficult cybersecurity tasks?
Version / measure
- Domain
- Cybersecurity
- Ranked models
- 4
- Reported values
- 4
- Reports
- 1 · lab
- Direction
- Higher is better
- Status
- Latest stable
Rankings
Best reported score per model across effort settings
| # | Model | Best setting | Score |
|---|---|---|---|
| 1 | GPT-6 AstraOpenAI | reportedcost n/a1 value · Sep 3 · source | 85.4% |
| 2 | GPT-5.6 SolOpenAI | maxcost n/a1 value · Sep 3 · source | 79.1% |
| 3 | GPT-6 SolOpenAI | reportedcost n/a1 value · Sep 22 · source | 66.3% |
| 4 | GPT-6 LunaOpenAI | reportedcost n/a1 value · Sep 22 · source | 34.2% |
Effort curve
Score vs. reported cost. Lines connect complete sweeps only.
No cost-linked effort sweep for this version.
Definition and comparison boundarylimited methodology
Can the model diagnose or complete difficult cybersecurity tasks?
Security analysis or exploitation under a controlled evaluation environment. Higher is better. The value is the percentage reported in this lab's table.
Harness, tools, prompts, attempt count, and benchmark version can materially change the result. Compare within one reporting context.
OpenAI reports GPT-6 Astra 85.4%, GPT-5.6 Sol at Max 79.1%, GPT-6 Sol 66.3%, and GPT-6 Luna 34.2%. The card does not specify the harness or effort for the GPT-6 Sol/Luna rows.
Method / source ↗