Code-Augur combines LLM-driven security specification inference with runtime falsification via guided fuzzing to improve vulnerability detection and reports finding 22 new vulnerabilities in open-source projects.
Locus: Agentic predicate synthesis for directed fuzzing,
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Proposes Secure Coding Drift as a longitudinal socio-technical vulnerability model for LLM-assisted PQC coding and a gamified mitigation framework.
citing papers explorer
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Code-Augur: Agentic Vulnerability Detection via Specification Inference
Code-Augur combines LLM-driven security specification inference with runtime falsification via guided fuzzing to improve vulnerability detection and reports finding 22 new vulnerabilities in open-source projects.
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Secure Coding Drift in LLM-Assisted Post-Quantum Cryptography Development: A Gamified Fix
Proposes Secure Coding Drift as a longitudinal socio-technical vulnerability model for LLM-assisted PQC coding and a gamified mitigation framework.