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CyberGym

Cybersecurity agent benchmark focused on vulnerability discovery tasks.

CyberGym
Image: AI-generated illustration (Seedream)

Cybersecurity agent benchmark focused on vulnerability discovery tasks. The table below lists 3 recorded evaluations across 3 models: deepseek-v4-1-flash, deepseek-v4-pro, glm-5.3. All entries are labeled by source type (vendor_reported) with links to the original publication. See the Limitations section for comparability caveats before citing any score.

Benchmark methodology

Methodology of CyberGym
Task type Cybersecurity vulnerability analysis (real-world vulnerability discovery)
Dataset size Large-scale task suite sourced from ARVO and OSS-Fuzz (~240GB data)
Evaluation method Docker-isolated environments; agents analyze vulnerabilities and generate proofs of concept; pre-/post-patch versions
Scoring Success rate on vulnerability analysis tasks (PoC generation)
Last verified: · Data status: Current · Next review:

Results

Results for CyberGym
Model Model version Score Metric Date Source type Source
deepseek-v4-1-flash 88.1 accuracy 2026-09-10 vendor_reported link
deepseek-v4-pro 83.3 accuracy 2026-08-13 vendor_reported link
glm-5.3 vuln discovery (GLM-5.2: 77.2) 84.5 accuracy 2026-08-18 vendor_reported link

Limitations

All scores are vendor-reported and not independently verified.

Vendor-reported scores are labeled as such. Scores from incompatible benchmark versions are never mixed without explanation.

Sources

What does CyberGym measure?

Cybersecurity agent benchmark focused on vulnerability discovery tasks.

Which Chinese AI models have published CyberGym results?

deepseek-v4-1-flash, deepseek-v4-pro, glm-5.3.

Are CyberGym scores independently verified?

Results on this page are labeled by source type (vendor_reported). Vendor-reported scores are labeled as such, and scores from incompatible benchmark versions are never mixed.

Where does China AI Hub get its CyberGym data?

From 3 sources, last verified 2026-09-20.