vLLM has RCE In Video Processing

Vulnerable Code Chain

1) Entry: vLLM accepts a remote video_url and downloads raw bytes

vLLM’s OpenAI-compatible API supports a video_url content part:

class VideoURL(TypedDict, total=False):
    url: Required[str]

class ChatCompletionContentPartVideoParam(TypedDict, total=False):
    video_url: Required[VideoURL]
    type: Required[Literal["video_url"]]

Source: src/vllm/entrypoints/chat_utils.py.

When the URL is HTTP(S), vLLM downloads it as raw bytes and passes the bytes into the modality loader:

if url_spec.scheme.startswith("http"):
    data = connection.get_bytes(url, timeout=fetch_timeout, allow_redirects=...)
    return media_io.load_bytes(data)

Source: src/vllm/multimodal/utils.py (MediaConnector.load_from_url).

2) Decode: vLLM uses OpenCV (cv2) VideoCapture on an in-memory byte stream

The default video backend is OpenCV, and it constructs cv2.VideoCapture over a BytesIO buffer containing the downloaded bytes:

backend = cls().get_cv2_video_api()
cap = cv2.VideoCapture(BytesIO(data), backend, [])
if not cap.isOpened():
    raise ValueError("Could not open video stream")

Source: src/vllm/multimodal/video.py (OpenCVVideoBackend.load_bytes).

The backend is selected from OpenCV’s stream-buffered backends registry:

import cv2.videoio_registry as vr
for backend in vr.getStreamBufferedBackends():
    if vr.hasBackend(backend) and ...:
        api_pref = backend
        break
return api_pref

Source: src/vllm/multimodal/video.py (OpenCVVideoBackend.get_cv2_video_api).

Implication: vLLM is delegating container parsing + codec decode to OpenCV’s Video I/O stack (which, in typical builds, is backed by FFmpeg for MOV/MP4 and codecs like JPEG2000).

3) The actual overflow: Y (full-res) written into U (quarter-res)

When the decoder honors the remap and writes Y into the U-plane buffer, it writes too many bytes:

• Y plane bytes: (W \times H)
• U plane bytes: ((W/2) \times (H/2))
• Overflow bytes: (W \times H - (W/2 \times H/2) = 0.75 \times W \times H)

Concrete example tried (150×64):

• Y: (150 \times 64 = 9600) bytes
• U: (75 \times 32 = 2400) bytes
• Overflow: (9600 - 2400 = 7200) bytes past the end of the U allocation

This is a heap buffer overflow into whatever allocations follow the U-plane buffer in the decoder’s heap layout (structures, metadata, other buffers, etc.). The exact victims depend on build + runtime allocator layout.

The Exploit Chain

Vuln 1: PIL BytesIO Address Leak (ASLR Bypass)

When you send an invalid image to vLLM's multimodal endpoint, PIL throws an error like:

cannot identify image file <_io.BytesIO object at 0x7a95e299e750>
                                                   ^^^^^^^^^^^^^^^^
                                                   LEAKED ADDRESS!

vLLM returns this error to the client, leaking a heap address. This address is ~10.33 GB before libc in memory. With this leak, we reduce ASLR from 4 billion guesses to ~8 guesses.

Vuln 2: JPEG2000 cdef Heap Overflow (RCE)

vLLM uses OpenCV (cv2) to decode videos. OpenCV bundles FFmpeg 5.1.x which has a heap overflow in the JPEG2000 decoder. The OpenCV is used for video decoding so if we build a video from JPEG2000 frames it will reach the vuln:

vLLM API Request to Completions/Invocation
     ↓
OpenCV cv2.VideoCapture()
     ↓
FFmpeg 5.1 (bundled in OpenCV)
     ↓
JPEG2000 decoder (libopenjp2)
     ↓
HEAP OVERFLOW via malicious "cdef" box
     ↓
Overwrite function pointer → RCE!

How the overflow works:

• JPEG2000 has a cdef box that remaps color channels
• We remap Y (luma) into the U (chroma) buffer
• Y plane = 9,600 bytes, U plane = 2,400 bytes
• On small geometry like 150x64 pixel image we get 7,200 bytes overflow past the U buffer. We can grow that exponentially by making bigger images.
• This overwrites an AVBuffer structure containing a free() function pointer. This could be any function pointer or other targets.
• We set free = system() and opaque = "command string"
• When the buffer is freed → system("our command") executes

vLLM Attack Surface

Affected Endpoints

Both multimodal endpoints are vulnerable:

POST /v1/chat/completions     (with video_url in content)
POST /v1/invocations          (with video_url in content)

Request Flow

1. Attacker sends request with video_url pointing to malicious .mov file
2. vLLM fetches the video from the URL
3. vLLM passes video bytes to cv2.VideoCapture()
4. OpenCV's bundled FFmpeg decodes JPEG2000 frames
5. Malicious cdef box triggers heap overflow
6. AVBuffer.free pointer overwritten with system()
7. When buffer is released → system("attacker command") executes

Versions Affected

Fixes

• https://github.com/vllm-project/vllm/pull/31987
• https://github.com/vllm-project/vllm/pull/32319
• https://github.com/vllm-project/vllm/pull/32668