Georgios Alexopoulos
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This paper demonstrates that LLM-based security code review systems are highly susceptible to sophisticated, iterative contextual bias attacks, which can successfully reintroduce vulnerabilities.
The paper introduces a provenance-aware vulnerability analysis approach that accurately identifies cross-ecosystem vulnerabilities in Python applications by resolving vendored native libraries to specific OS package versions, significantly reducing false positives.
Papers
Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review
This paper demonstrates that LLM-based security code review systems are highly susceptible to sophisticated, iterative contextual bias attacks, which can successfully reintroduce vulnerabilities.