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LLMs not only introduce new vulnerabilities but also amplify existing web threats, necessitating a paradigm shift in how we secure online interactions.
JITterFlip reveals that targeting the JIT serving control plane can amplify attack effects by over 7 million times, exposing a major vulnerability in LLM inference systems.
Real-world complexities expose significant performance gaps in autonomous agents, revealing that even advanced LLMs struggle with task completion in dynamic environments.
