Infinite agentic loops are a distinct failure mode in LLM agents arising from unbounded feedback paths, and IAL-Scan detects them via framework-independent static analysis with 91.9% precision on 6,549 repositories.
AgentRaft: Automated detection of data over-exposure in LLM agents,
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PrivacyPeek is a benchmark with 1,182 cases across 7 acquisition behaviors and 16 domains that evaluates acquisition-stage privacy leakage in LLM agents, finding it widespread with limited prompt mitigation.
SkillScope detects over-privileged LLM agent skills with 94.53% F1 score via graph analysis and replay validation, finding 7,039 problematic skills in the wild and reducing violations by 88.56% while preserving task completion.
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SkillScope: Toward Fine-Grained Least-Privilege Enforcement for Agent Skills
SkillScope detects over-privileged LLM agent skills with 94.53% F1 score via graph analysis and replay validation, finding 7,039 problematic skills in the wild and reducing violations by 88.56% while preserving task completion.