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StateLens is presented, a framework that employs Large Language Models (LLM) to automate the discovery of deep internal states in JS engines and significantly outperforms state-of-the-art fuzzers and uncovering 68 new bugs.
This work proposes Collision Mesh Poisoning (CMP), the first poisoning attack against robotic manipulation delivered through the 3D asset supply chain, and evaluates several defenses and shows that they are insufficient to defend against CMP, highlighting the need for new defenses.
LLMs can proactively unearth silent bugs in deep learning libraries by transferring bug patterns from historical reports to similar APIs, finding 79 previously unknown bugs.
