
In a groundbreaking discovery, cybersecurity researchers have brought to light a novel side-channel attack known as "InputSnatch," which poses a significant threat to user privacy as individuals interact with large language models (LLMs). This newly identified attack exploits timing discrepancies in cache-sharing mechanisms—tools that are often employed to enhance LLM inference performance—to expropriate input data. Remarkably, the attack can specifically