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S&P2023

Number of papers: 1

  • Authors: Pearce, Hammond and Tan, Benjamin and Ahmad, Baleegh and Karri, Ramesh and Dolan-Gavitt, Brendan
  • Abstract: Human developers can produce code with cybersecurity bugs. Can emerging ‘smart’ code completion tools help repair those bugs? In this work, we examine the use of large language models (LLMs) for code (such as OpenAI’s Codex and AI21’s Jurassic J-1) for zero-shot vulnerability repair. We investigate challenges in the design of prompts that coax LLMs into generating repaired versions of insecure code. This is difficult due to the numerous ways to phrase key information— both semantically and synta...
  • Link: Read Paper
  • Labels: static analysis, bug detection, empirical study