Bit-Flip Vulnerability of Shared KV-Cache Blocks in LLM Serving Systems

Rowhammer on GPU DRAM has enabled adversarial bit flips in model weights; shared KV-cache blocks in LLM serving systems present an analogous but previously unexamined target. In vLLM's Prefix Caching, these blocks exist as a single physical copy without integrity protection. Using software fault...

CVE-2025-60455

Unsafe Deserialization vulnerability in Modular Max Serve before 25.6, specifically when the "--experimental-enable-kvcache-agent" feature is used allowing attackers to execute arbitrary code...

Can Transformer Memory Be Corrupted? Investigating Cache-Side Vulnerabilities in Large Language Models

Even when prompts and parameters are secured, transformer language models remain vulnerable because their key-value KV cache during inference constitutes an overlooked attack surface. This paper introduces Malicious Token Injection MTI, a modular framework that systematically perturbs cached key...

CVE-2025-47277

vLLM, an inference and serving engine for large language models LLMs, has an issue in versions 0.6.5 through 0.8.4 that ONLY impacts environments using the PyNcclPipe KV cache transfer integration with the V0 engine. No other configurations are affected. vLLM supports the use of...

CVE-2025-47277

vLLM, an inference and serving engine for large language models LLMs, has an issue in versions 0.6.5 through 0.8.4 that ONLY impacts environments using the "PyNcclPipe" KV cache transfer integration with the V0 engine. No other configurations are affected. vLLM supports the use of...

CVE-2025-47277 vLLM Allows Remote Code Execution via PyNcclPipe Communication Service

vLLM, an inference and serving engine for large language models LLMs, has an issue in versions 0.6.5 through 0.8.4 that ONLY impacts environments using the PyNcclPipe KV cache transfer integration with the V0 engine. No other configurations are affected. vLLM supports the use of...

CVE-2025-47277: Deserialization of Untrusted Data

vLLM, an inference and serving engine for large language models LLMs, has an issue in versions 0.6.5 through 0.8.4 that ONLY impacts environments using the PyNcclPipe KV cache transfer integration with the V0 engine. No other configurations are affected. vLLM supports the use of...

PT-2025-22278

Name of the Vulnerable Software and Affected Versions vLLM versions 0.6.5 through 0.8.4 Description vLLM, an inference and serving engine for large language models LLMs, contains a remote code execution issue. This impacts environments utilizing the PyNcclPipe KV cache transfer integration with t...