Описание
vLLM: OOM Denial of Service via Audio Decompression Bomb
Summary
vLLM's /v1/audio/transcriptions endpoint limits compressed upload size but not decoded PCM output. A 25MB OPUS file expands to ~14.9GB of float32 PCM at decode time. Tested on vLLM v0.19.0.
Details
SpeechToTextProcessor rejects uploads over VLLM_MAX_AUDIO_CLIP_FILESIZE_MB (default 25MB) based on compressed byte length, but the audio decoder in audio.py accumulates all decoded frames into memory with no size limit before returning:
A 25MB OPUS file at 6kbps encodes ~8.7 hours of audio. Decoding produces ~5.7GB of float32 PCM (232x amplification), and np.concatenate then allocates a second contiguous array, bringing peak RSS to ~14.9GB from a single request. SpeechToTextConfig.max_audio_clip_s (default 30s) applies only after the full decode and does not prevent the allocation.
Impact
An unauthenticated attacker can exhaust server memory with a small number of concurrent requests, each a valid upload within the documented size limit. Severity was assessed with reference to prior OOM vulnerability reports in vLLM.
Fix
A fix for this vulnerability was merged here: https://github.com/vllm-project/vllm/pull/44970
Ссылки
- https://github.com/vllm-project/vllm/security/advisories/GHSA-6pr9-rp53-2pmc
- https://nvd.nist.gov/vuln/detail/CVE-2026-54233
- https://github.com/vllm-project/vllm/pull/44970
- https://github.com/vllm-project/vllm/commit/1b1359c33269446f13c05da9a90c25174cbea590
- https://github.com/advisories/GHSA-6pr9-rp53-2pmc
- https://github.com/pypa/advisory-database/tree/main/vulns/vllm/PYSEC-2026-3404.yaml
- https://github.com/vllm-project/vllm/releases/tag/v0.23.1rc0
- https://pypi.org/project/vllm
Пакеты
vllm
<= 0.23.0
0.24.0
Связанные уязвимости
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, vLLM's /v1/audio/transcriptions endpoint limits compressed upload size but not decoded PCM output. A 25MB OPUS file expands to ~14.9GB of float32 PCM at decode time. This vulnerability is fixed in 0.23.1rc0.
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, vLLM's /v1/audio/transcriptions endpoint limits compressed upload size but not decoded PCM output. A 25MB OPUS file expands to ~14.9GB of float32 PCM at decode time. This vulnerability is fixed in 0.23.1rc0.
vLLM is an inference and serving engine for large language models (LLM ...