AWS’ Deception Benchmark measures how well AI models distinguish genuine security vulnerabilities from code that looks risky but is safe. AWS is making it publicly available so researchers can use the dataset and evaluation process without repeating the cost of generating and refining the samples. Security teams use AI for vulnerability triage, penetration testing, threat modeling, incident response, and code review. High false-positive rates can create more work, increase alert fatigue, and reduce confidence in … More →
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