CVE-2026-55646

vLLM is an inference and serving engine for large language models. From 0.22.0 to 0.23.0, the /v1/audio/transcriptions and /v1/audio/translations routes call request.file.read() to fully materialize an uploaded audio file into memory before vLLM checks the documented VLLM_MAX_AUDIO_CLIP_FILESIZE_MB compressed upload size limit (default 25 MB) later in the speech-to-text preprocessing step, so an API caller who can reach those routes can submit an oversized multipart upload and cause vLLM to allocate memory proportional to the uploaded file size before the request is rejected as too large, creating memory pressure or terminating the process depending on deployment resource limits. This issue is fixed in version 0.24.0.

vLLM is an inference and serving engine for large language models. From 0.22.0 to 0.23.0, the /v1/audio/transcriptions and /v1/audio/translations routes call request.file.read() to fully materialize an uploaded audio file into memory before vLLM checks the documented VLLM_MAX_AUDIO_CLIP_FILESIZE_MB compressed upload size limit (default 25 MB) later in the speech-to-text preprocessing step, so an API caller who can reach those routes can submit an oversized multipart upload and cause vLLM to allocate memory proportional to the uploaded file size before the request is rejected as too large, creating memory pressure or terminating the process depending on deployment resource limits. This issue is fixed in version 0.24.0.

Summary

Current-head vLLM documents VLLM_MAX_AUDIO_CLIP_FILESIZE_MB as the maximum audio file size accepted by the speech-to-text APIs. The default is 25 MB. vllm/envs.py also describes files larger than this value as rejected.

The /v1/audio/transcriptions and /v1/audio/translations routes call await request.file.read() before vLLM checks that limit. In FastAPI and Starlette, UploadFile.read() returns bytes from the uploaded file object; when called without a size argument, the route materializes the remaining file contents. vLLM then performs the compressed file-size check later in _preprocess_speech_to_text() against the already-created bytes object.

As a result, the documented compressed audio file-size limit does not bound the memory allocated by vLLM endpoint code before validation. An oversized multipart upload can cause vLLM to allocate memory proportional to the uploaded file size before rejecting the request as too large.

This is distinct from GHSA-6pr9-rp53-2pmc, which covered decoded PCM expansion after compressed input was accepted. This report covers compressed upload materialization before compressed-size validation.

Technical Details

The upload routes perform an unbounded read before vLLM checks the documented compressed audio file-size limit:

• vllm/entrypoints/speech_to_text/transcription/api_router.py: audio_data = await request.file.read()
• vllm/entrypoints/speech_to_text/translation/api_router.py: audio_data = await request.file.read()
• vllm/entrypoints/speech_to_text/base/serving.py later checks: if len(audio_data) / 1024**2 > self.max_audio_filesize_mb

There is no route-level check of request.file.size, Content-Length, a bounded read(max_bytes + 1), or a streaming copy that stops at the configured limit before the full file is materialized.

This does not appear to be intended behavior. vLLM's security guide treats request-controlled resource use as a security boundary: for example, requests that exceed VLLM_MAX_N_SEQUENCES are rejected before reaching the engine. The speech-to-text upload limit is documented in the same spirit as an API enforced limit, but the first vLLM check happens after the over-limit upload has already been copied into a bytes object.

Impact

Attack requirements:

• the deployment exposes /v1/audio/transcriptions or /v1/audio/translations;
• a speech-to-text capable model/task is configured; and
• the caller can submit requests to the endpoint, including any API key the deployment requires.

An API caller who meets those requirements can send an oversized audio file. vLLM reads the full uploaded file into memory before applying the configured compressed audio file-size limit. This can create memory pressure or, depending on process/container limits and concurrency, terminate the process before the request is rejected.

Suggested severity: Moderate, CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H (6.5), CWE-770/CWE-400.

The impact is availability-only. This is not a claim of code execution, data access, cross-tenant data exposure, parser-level multipart memory exhaustion, or persistence after process restart. Deployment body-size limits at a reverse proxy or ASGI layer can mitigate the issue before vLLM sees the request, but vLLM's own documented file-size limit does not currently provide that memory boundary.

Suggested Fix

Enforce the compressed audio upload limit before the unbounded read:

• Check reliable upload size metadata before reading when available.
• Read at most max_bytes + 1 bytes in chunks as a defense-in-depth guard against missing or unreliable metadata.
• Share the helper between transcription and translation routes.
• Add regression tests that prove an over-limit UploadFile is rejected without calling an unbounded read().

The important property is that over-limit compressed uploads are rejected before vLLM allocates the full uploaded file as bytes.

Resources

• vLLM security…

vLLM is an inference and serving engine for large language models. From 0.22.0 to 0.23.0, the /v1/audio/transcriptions and /v1/audio/translations routes call request.file.read() to fully materialize an uploaded audio file into memory before vLLM checks the documented VLLM_MAX_AUDIO_CLIP_FILESIZE_MB compressed upload size limit (default 25 MB) later in the speech-to-text preprocessing step, so an API caller who can reach those routes can submit an oversized multipart upload and cause vLLM to allocate memory proportional to the uploaded file size before the request is rejected as too large, creating memory pressure or terminating the process depending on deployment resource limits. This issue is fixed in version 0.24.0.

vLLM is an inference and serving engine for large language models. From 0.22.0 to 0.23.0, the /v1/audio/transcriptions and /v1/audio/translations routes call request.file.read() to fully materialize an uploaded audio file into memory before vLLM checks the documented VLLM_MAX_AUDIO_CLIP_FILESIZE_MB compressed upload size limit (default 25 MB) later in the speech-to-text preprocessing step, so an API caller who can reach those routes can submit an oversized multipart upload and cause vLLM to allocate memory proportional to the uploaded file size before the request is rejected as too large, creating memory pressure or terminating the process depending on deployment resource limits. This issue is fixed in version 0.24.0.

Summary

Current-head vLLM documents VLLM_MAX_AUDIO_CLIP_FILESIZE_MB as the maximum audio file size accepted by the speech-to-text APIs. The default is 25 MB. vllm/envs.py also describes files larger than this value as rejected.

The /v1/audio/transcriptions and /v1/audio/translations routes call await request.file.read() before vLLM checks that limit. In FastAPI and Starlette, UploadFile.read() returns bytes from the uploaded file object; when called without a size argument, the route materializes the remaining file contents. vLLM then performs the compressed file-size check later in _preprocess_speech_to_text() against the already-created bytes object.

As a result, the documented compressed audio file-size limit does not bound the memory allocated by vLLM endpoint code before validation. An oversized multipart upload can cause vLLM to allocate memory proportional to the uploaded file size before rejecting the request as too large.

This is distinct from GHSA-6pr9-rp53-2pmc, which covered decoded PCM expansion after compressed input was accepted. This report covers compressed upload materialization before compressed-size validation.

Technical Details

The upload routes perform an unbounded read before vLLM checks the documented compressed audio file-size limit:

• vllm/entrypoints/speech_to_text/transcription/api_router.py: audio_data = await request.file.read()
• vllm/entrypoints/speech_to_text/translation/api_router.py: audio_data = await request.file.read()
• vllm/entrypoints/speech_to_text/base/serving.py later checks: if len(audio_data) / 1024**2 > self.max_audio_filesize_mb

There is no route-level check of request.file.size, Content-Length, a bounded read(max_bytes + 1), or a streaming copy that stops at the configured limit before the full file is materialized.

This does not appear to be intended behavior. vLLM's security guide treats request-controlled resource use as a security boundary: for example, requests that exceed VLLM_MAX_N_SEQUENCES are rejected before reaching the engine. The speech-to-text upload limit is documented in the same spirit as an API enforced limit, but the first vLLM check happens after the over-limit upload has already been copied into a bytes object.

Impact

Attack requirements:

• the deployment exposes /v1/audio/transcriptions or /v1/audio/translations;
• a speech-to-text capable model/task is configured; and
• the caller can submit requests to the endpoint, including any API key the deployment requires.

An API caller who meets those requirements can send an oversized audio file. vLLM reads the full uploaded file into memory before applying the configured compressed audio file-size limit. This can create memory pressure or, depending on process/container limits and concurrency, terminate the process before the request is rejected.

Suggested severity: Moderate, CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H (6.5), CWE-770/CWE-400.

The impact is availability-only. This is not a claim of code execution, data access, cross-tenant data exposure, parser-level multipart memory exhaustion, or persistence after process restart. Deployment body-size limits at a reverse proxy or ASGI layer can mitigate the issue before vLLM sees the request, but vLLM's own documented file-size limit does not currently provide that memory boundary.

Suggested Fix

Enforce the compressed audio upload limit before the unbounded read:

• Check reliable upload size metadata before reading when available.
• Read at most max_bytes + 1 bytes in chunks as a defense-in-depth guard against missing or unreliable metadata.
• Share the helper between transcription and translation routes.
• Add regression tests that prove an over-limit UploadFile is rejected without calling an unbounded read().

The important property is that over-limit compressed uploads are rejected before vLLM allocates the full uploaded file as bytes.

Resources

• vLLM security…

vLLM is an inference and serving engine for large language models. From 0.22.0 to 0.23.0, the /v1/audio/transcriptions and /v1/audio/translations routes call request.file.read() to fully materialize an uploaded audio file into memory before vLLM checks the documented VLLM_MAX_AUDIO_CLIP_FILESIZE_MB compressed upload size limit (default 25 MB) later in the speech-to-text preprocessing step, so an API caller who can reach those routes can submit an oversized multipart upload and cause vLLM to allocate memory proportional to the uploaded file size before the request is rejected as too large, creating memory pressure or terminating the process depending on deployment resource limits. This issue is fixed in version 0.24.0.