arXiv AI By Dimitris Mitropoulos, Nikolaos Alexopoulos, Georgios Alexopoulos, Diomidis Spinellis

Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review

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arXiv AI
Aug 18

Workspace Topology as an Attack Vector in Agentic Coding Assistants

arXiv:2608. 14876v1 Announce Type: cross Abstract: Agentic coding assistants are finding widespread use, not just in new code development but in quickly ingesting and leveraging third-party code.

By Alexandre G. R. Day, Pradeep Yadlapalli, Sriram Venkatapathy, Thomas Paniagua, Nick Raines, Sahil Wadhwa, Himanshu Kumar, Andy Luo, Sudeep Panyam, Rikhiya Ghosh, Pranab Mohanty, Giri Iyengar
arXiv Machine Learning
Sep 3

CodePoisonRAG: Knowledge Poisoning Attacks on Retrieval-Augmented Code Generation

The paper introduces CodePoisonRAG, a framework that poisons retrieval-augmented code generation systems by transforming benign code artifacts into malicious ones. It injects CWE-specific vulnerabilities and false safety claims into a single task-matched artifact, achieving high success rates across multiple generators and even against a defense system. The study demonstrates that attackers can target and propagate specific weaknesses without altering the underlying language model.

By Varun Gadey, Ziad Marey, Alexandra Dmitrienko