AuditBench - Lab Exfiltration: leaderboard

AuditBench (2026) evaluates LLMs on security investigations over system audit logs read in 400-line chunks. This board is the F1 score (0 to 100) for finding the log lines of data exfiltration in the 5 attack scenarios of the Lab data (Linux and Windows audit logs recorded by the benchmark authors). Higher is better.

Metric: F1 (0-100) for data-exfiltration identification on the Lab data (Linux and Windows audit logs recorded by the authors) (5 attack scenarios): the model reads the scenario's edge-representation (provenance-graph edges, 400-line chunks) audit logs in chunks with prompt v2 and flags the log lines of the exfiltration; recall counts the attack scenarios found and precision counts false-positive log lines; temperature 0 where available (GPT-5 models at the default medium reasoning effort); higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 5 models tracked.

Top models

#ModelScoreOverall rank
1GPT-577#167
2Gemini 2.5 Flash56#453
3GPT-5 Mini50#348
4Gemini 2.5 Pro40#266
5Llama 4 Maverick29#1099

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=auditbench-lab-exfiltration · How It Works · Data refreshed daily, snapshot 2026-11-13.