SKILLSCOPE detects undisclosed security behaviors in LLM skill implementations via security property graphs and taxonomy-based consistency checking, identifying confirmed inconsistencies in 9.4% of 4,556 evaluated skills with 84.8% precision and 96.5% recall against human review.
Large language models versus static code analysis tools: A systematic benchmark for vulnerability detection,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CR 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Do Skill Descriptions Tell the Truth? Detecting Undisclosed Security Behaviors in Code-Backed LLM Skills
SKILLSCOPE detects undisclosed security behaviors in LLM skill implementations via security property graphs and taxonomy-based consistency checking, identifying confirmed inconsistencies in 9.4% of 4,556 evaluated skills with 84.8% precision and 96.5% recall against human review.