Vllm Project Vllm
Monthly
Denial of service in vLLM 0.8.0 and later allows remote unauthenticated attackers to crash the inference server by sending a single OpenAI-compatible chat completion request containing a video/jpeg data URL with thousands of comma-separated base64-encoded JPEG frames. The VideoMediaIO.load_base64() method decodes every frame without enforcing a count limit, exhausting server memory. No public exploit identified at time of analysis, but an upstream fix commit is available on GitHub.
Remote code execution in vLLM 0.14.1 occurs because `trust_remote_code=True` is hardcoded inside the NemotronVL and KimiK25 model loaders, silently overriding the operator's explicit `--trust-remote-code=False` safety flag. Any deployment that loads a malicious or compromised HuggingFace repository for these model architectures will execute attacker-controlled Python in the inference process, despite UI:R requiring an operator to initiate the model load. No public exploit is identified at time of analysis, but the issue is an incomplete fix for CVE-2025-66448 and CVE-2026-22807, indicating the regression pattern is already well understood.
Denial of service in vLLM 0.8.0 and later allows remote unauthenticated attackers to crash the inference server by sending a single OpenAI-compatible chat completion request containing a video/jpeg data URL with thousands of comma-separated base64-encoded JPEG frames. The VideoMediaIO.load_base64() method decodes every frame without enforcing a count limit, exhausting server memory. No public exploit identified at time of analysis, but an upstream fix commit is available on GitHub.
Remote code execution in vLLM 0.14.1 occurs because `trust_remote_code=True` is hardcoded inside the NemotronVL and KimiK25 model loaders, silently overriding the operator's explicit `--trust-remote-code=False` safety flag. Any deployment that loads a malicious or compromised HuggingFace repository for these model architectures will execute attacker-controlled Python in the inference process, despite UI:R requiring an operator to initiate the model load. No public exploit is identified at time of analysis, but the issue is an incomplete fix for CVE-2025-66448 and CVE-2026-22807, indicating the regression pattern is already well understood.