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SRE-Bench exposes AI’s binary-analysis gap

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SRE-Bench exposes AI’s binary-analysis gap
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// 1h agoRESEARCH PAPER

SRE-Bench exposes AI’s binary-analysis gap

Columbia researchers introduce SRE-Bench, a contamination-free benchmark testing AI agents on real-scale binary reverse engineering without source code. Its 262 protected binaries and 1,572 deterministic tasks show frontier agents still struggle to recover program semantics reliably.

// ANALYSIS

SRE-Bench is a much-needed reality check for cybersecurity agents: strong source-code performance does not automatically transfer to compiled software.

  • –19 private programs and 44 anti-analysis mechanisms reduce memorization and shortcutting
  • –The strongest initial model fully solved only 31.5% of instances
  • –Tasks span malware, firmware, proprietary software, and other realistic reverse-engineering scenarios
  • –Agents’ relative insensitivity to optimization and static linking suggests pattern matching remains a major weakness
  • –Deterministic grading makes the benchmark more meaningful than evaluations based on plausible explanations
// TAGS
sre-benchevaluationbenchmarksecurityresearchagentdataset

DISCOVERED

1h ago

2026-10-06

PUBLISHED

1h ago

2026-10-06

RELEVANCE

9/ 10

AUTHOR

AI Search