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Evidence record

Claude Sonnet 3.7 · Anthropic Agent

CyberGym · Evidence record

Sources and provenance ↓ Read the research narrative →

Source snapshot, chart and review scope →

Original source charts and materials

Recorded measurements

Success rate
47.2%

Per-result sample size not disclosed

Anthropic Agent · Budget not specified

Method and scope

Validated reproduction across a corpus of historical vulnerabilities.

Evidence type
Benchmark
Assessment subject
AI agent reproducing historical vulnerabilities
Primary dimension
Capability
Evidence snapshot
2026-10-29.1

Primary dimension follows the source’s measured construct. Metric-level interpretations may differ.

Source finding

The source reports the fraction 0.472. The displayed 47.2% follows multiplication by 100 and rounding to 1 decimal place(s).

Limitations

Vulnerability reproduction is narrower than autonomous compromise of deployed systems.

The score_10 field name does not specify ten trials. Unknown budgets and per-row denominators remain unknown. Team-submitted leaderboard result; no per-row execution receipt or independent reproduction in this extraction. Row denominator, benchmark revision/subset, actual execution date and per-row resource budgets are not disclosed. Source label and URL do not establish the actual executor, developer or submitter. Thirty attempts per instance; omitted by the current single-trial UI selector. Do not compare as one-trial results.

Original figure retained without estimating numerical values. Full source tables have not been transcribed.

Related research questions

References

  1. [1] Zhun Wang, Tianneng Shi, et al.. CyberGym: Evaluating AI Agents' Real-World Cybersecurity Capabilities at Scale. 2026-03-24. v3 [arXiv]; Author affiliations on the original paper title page; Figure 2
  2. [2] CyberGym official leaderboard and machine-data extraction ; /level1/66/score_10