AI · 2h ago
Red-teaming AI: Why reading model replies matters more than attack success rates
A developer built a red-team test suite for LLM APIs and found that standard attack success rate (ASR) metrics overcount real harm. In one test, garak reported ~100% ASR, but manual review showed only 2% of replies contained actionable content. The project highlights that detecting guardrail bypasses is easier than assessing actual harm.
Meridian48 take
The piece underscores a critical blind spot in AI safety testing: automated detectors often flag harmless outputs as breaches, while real risks slip through—a problem that demands more human oversight, not just better metrics.
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The hard part of attacking an AI isn't breaking it. It's telling real harm from fake. →
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