CVE-2026-105753

vLLM before 0.29.0 passes uploaded audio to the PyAV/FFmpeg av.open() fallback with only a file-size check, exposing FFmpeg's IAMF parser heap overflow. Authenticated remote attackers can repeatedly upload malformed IAMF containers to /v1/audio/transcriptions, corrupting the heap and crashing the API process.

Vulnerability in vLLM versions 0.3.0 to 0.22.0 allows bypass of OpenAI API AuthenticationMiddleware. An attacker can use the API without providing the configured VLLM_API_KEY or --api-key.

A vulnerability in vLLM from version 0.8.3 to 0.14.0 leaks a heap address when an invalid image is sent to the multimodal endpoint. This leak reduces ASLR effectiveness from 4 billion to about 8 guesses, facilitating further attacks.

A security flaw has been discovered in vllm-project vLLM up to 0.31.0, affecting the function get_token_bin_counts_and_mask in the file vllm/model_executor/layers/utils.py of the Penalty Handler component. Manipulation results in denial of service. Remote exploitation is possible, and the exploit has been publicly released.

A security vulnerability in vllm-project vLLM up to 0.31.0 causes an out-of-bounds read in the function conv_ssm_forward in the file mamba_mixer2.py, within the Completions Request Handler component. The attack can be carried out remotely, and the exploit has been publicly disclosed.

In vLLM before 0.30.0, a caller can use the media_io_kwargs field to select the GLMGA video backend and supply large fps and max_frames values without a strict work ceiling, causing disproportionate CPU and memory consumption.

In vLLM before 0.30.0, the Rust frontend's track_http_metrics middleware records the raw HTTP method token as a Prometheus label, allowing an unauthenticated attacker to send unique arbitrary method tokens and cause permanent creation of label sets, increasing memory usage.

In vLLM from 0.24.0 to 0.30.0, the Qwen2VLVideoBackend and Qwen3VLVideoBackend classes accept request-level values for max_frames and fps without server-side ceilings, allowing an unauthenticated caller to decode every frame from attacker-controlled video and consume disproportionate memory.

In vLLM before 0.30.0, structured-output request failures can escape validation and reach the EngineCore fatal-error path, allowing ordinary constrained-generation requests to terminate the shared engine.

In vLLM before 0.30.0, OpenAI-compatible request models accept a non-empty cache_salt value without enforcing character and length restrictions, which can raise an uncaught ValueError during scheduler cache lookup, causing EngineCore to terminate.