When "Correct" Is Not Safe: Can We Trust Functionally Correct Patches
  Generated by Code Agents?
Authors: name: Yibo Peng, name: James Song, name: Lei Li, name: Xinyu Yang, name: Mihai Christodorescu, name: Ravi Mangal, name: Corina Pasareanu, name: Haizhong Zheng, name: Beidi Chen

Code agents are increasingly trusted to autonomously fix bugs on platforms
such as GitHub, yet their security evaluation focuses almost exclusively on
functional correctness. In this paper, we reveal a novel type of threat to
real-world code agents: Functionally Correct yet Vulnerable (FCV) patches,
which pass all test cases but contain vulnerable code. With our proposed
FCV-Attack, which can be deliberately crafted by malicious attackers or
implicitly introduced by benign developers, we show that SOTA LLMs (e.g.,
ChatGPT and Claude) and agent scaffolds (e.g., SWE-agent and OpenHands) are all
vulnerable to this FCV threat; across 12 agent-model combinations on SWE-Bench,
the attack only requires black-box access and a single query to the code agent
to perform the attack. For example, for CWE-538 (information exposure
vulnerability), the FCV-Attack attains an attack success rate of 40.7% on
GPT-5 Mini + OpenHands. Our results reveal an important security threat
overlooked by current evaluation paradigms and urge the development of
security-aware defenses for code agents.