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cs.CR2026
MetaVul: Agentic Harness Discovery for Vulnerability Detection
Ira Ceka, Arnav Garg, Ryan Lutz +4
LLM agents are increasingly used to automate vulnerability detection, but reliable detection is challenging because agents must distinguish subtle, security-relevant fixes from ben…
cs.CR2024
Can LLM Prompting Serve as a Proxy for Static Analysis in Vulnerability Detection
Ira Ceka, Feitong Qiao, Anik Dey +3
Despite their remarkable success, large language models (LLMs) have shown limited ability on safety-critical code tasks such as vulnerability detection. Typically, static analysis…
cs.CR2023
Vignat: Vulnerability identification by learning code semantics via graph attention networks
Shuo Liu, Gail Kaiser
Vulnerability identification is crucial to protect software systems from attacks for cyber-security. However, huge projects have more than millions of lines of code, and the comple…