Neo combines LLM-based agents with code search primitives to detect privilege escalation in polyglot microservices, reporting 81% precision and 85% recall while uncovering 24 zero-day vulnerabilities across 25 applications.
Modeling and discovering vulnerabilities with code property graphs,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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cs.CR 2years
2026 2representative citing papers
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.
citing papers explorer
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Detecting Privilege Escalation in Polyglot Microservices via Agentic Program Analysis
Neo combines LLM-based agents with code search primitives to detect privilege escalation in polyglot microservices, reporting 81% precision and 85% recall while uncovering 24 zero-day vulnerabilities across 25 applications.
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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.