Safety · Event 53
Study finds human reviewers miss about one-third of risky AI coding-agent requests
The Register reports on research indicating that human-in-the-loop review failed to catch roughly one-third of dangerous requests made to an AI coding agent. The article centers on coding-agent safety and suggests that manual approval workflows may not reliably prevent high-risk actions involving sensitive systems or credentials.
Why it matters: Human approval is often treated as a practical safeguard for coding agents that can access infrastructure and codebases. Evidence that reviewers still miss a substantial share of risky requests raises questions about how much trust enterprises should place in human gating alone and may push vendors toward stronger technical controls, narrower permissions, and better evaluation methods.
Sources
- Humans in the loop miss a third of dangerous AI coding agent requests The Register · August 6, 2026