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LLM Atlas

Benchmarks

CyberSecEval

deprecatedCodingcontamination risk: highlaunched 2023-12-07

Benchmark metadata from benchwiki — this page mirrors their record so scores can be joined to it. The original is canonical.

Superseded by cyberseceval-4.

What it measures

Meta's evolving suite for insecure code, cyberattack assistance, prompt injection, exploitation, SOC analysis, and autopatching.

Primary metric
average textual prompt-injection success rate (%) — lower is safer
Judge model
not judged by a model
Human baseline
not reportedNo suite-wide human baseline exists. Some components use human-written or expert-derived labels, but their scores and task definitions are not one comparable human axis.
Languages
Multilingual

Health

The structured leaderboard axis is BenchmarkList's seven-model textual prompt-injection snapshot sampled 2026-05-27. Timeline dates are official model launch dates, not score-evaluation dates. Lower scores are safer. Comparability depends on the exact CyberSecEval prompt set, judge, model interface, and guardrail configuration. Other CyberSecEval modules remain separate axes.

Status evidence
The original CyberSecEval benchmark is no longer the recommended standalone version: Meta advanced through CyberSecEval 2 and 3 to CyberSecEval 4, changing tasks and metrics rather than maintaining one comparable score axis.
Saturated since
not saturated
Refresh cycle
static
Test set public
yes

Versioned additions broaden coverage, but most prompts and labels are public. Agentic cyber-range tasks add live environment variation; evaluators should version data and keep any private cases separate.

Models scored on this benchmark

The reverse lookup, which is this site’s addition: every model here with a score on this benchmark. Independent measurements and vendor-reported numbers are kept apart rather than interleaved, because they are different claims.

No model on this site has a score on this benchmark yet. That usually means the models that were measured on it are not in the registry, rather than that nobody has run it.

Trajectory

UN codellama-70b-instruct — 12.93 on 2024-01-29 (vendor-reported)gpt-4 — 19.87 on 2023-03-14 (vendor-reported)llama 3 70b-instruct — 29.27 on 2024-04-18 (vendor-reported)UN codellama-34b-instruct — 36.33 on 2023-08-24 (vendor-reported)UN codellama-13b-instruct — 37.27 on 2023-08-24 (vendor-reported)gpt-3.5-turbo — 39.13 on 2023-03-01 (vendor-reported)llama 3 8b-instruct — 45.27 on 2024-04-18 (vendor-reported)20242024450
independent · vendor-reported. Points are not joined: the scores come from different models, harnesses and protocol versions, and a line between them would claim a continuity the data does not have.

Where results are tracked

Leaderboards benchwiki lists for this benchmark. These are links out, not sources this site ingests — no score below comes from any of them.

Source

This record is maintained by benchwiki and mirrored here. Read the original. Upstream last updated 2026-08-03; fetched 2026-10-19 by this site.