5 citations · 12 across the 15 of their papers we have counts for
4 papers · 1 filter
AKRASIA: Stealthy Backdoor Attack on Reasoning-based Code LLMs
Chua Jin Chou, Sarang Nambiar, Murali Srinivasan +1
We present AKRASIA, a stealthy, inference-time backdoor attack against reasoning-based Code LLMs. AKRASIA aims to achieve a backdoor target (e.g., malicious code execution) in reas…
ShadowPickle: Evading Machine Learning Model Scanners via Stealthy Pickle Deserialization Attacks
Dhruv Pradhan, Sarang Nambiar, Ezekiel Soremekun
Model hosting hubs (e.g., Hugging Face) are vulnerable to supply chain attacks that enable remote code execution on trusted user environments. Attackers often distribute malicious…
Malicious ML Model Detection by Learning Dynamic Behaviors
Sarang Nambiar, Dhruv Pradhan, Ezekiel Soremekun
Pre-trained machine learning models (PTMs) are commonly provided via Model Hubs (e.g., Hugging Face) in standard formats like Pickles to facilitate accessibility and reuse. However…
MUCOCO: Automated Consistency Testing of Code LLMs
Chua Jin Chou, Khant That Lwin, Ezekiel Soremekun
Code LLMs often portray inconsistent program behaviors. Developers typically employ benchmarks to assess Code LLMs, but most benchmarks are hand-crafted, static and do not target c…