CVE-2026-34755

The VideoMediaIO.load_base64() method at vllm/multimodal/media/video.py:51-62 splits video/jpeg data URLs by comma to extract individual JPEG frames, but does not enforce a frame count limit. The num_frames parameter (default: 32), which is enforced by the load_bytes() code path at line 47-48, is completely bypassed in the video/jpeg base64 path. An attacker can send a single API request containing thousands of comma-separated base64-encoded JPEG frames, causing the server to decode all frames into memory and crash with OOM.

Details

Vulnerable code

# video.py:51-62
def load_base64(self, media_type: str, data: str) -> tuple[npt.NDArray, dict[str, Any]]:
    if media_type.lower() == "video/jpeg":
        load_frame = partial(self.image_io.load_base64, "image/jpeg")
        return np.stack(
            [np.asarray(load_frame(frame_data)) for frame_data in data.split(",")]
            #                                                       ^^^^^^^^^^
            # Unbounded split, no frame count limit
        ), {}
    return self.load_bytes(base64.b64decode(data))

The load_bytes() path (line 47-48) properly delegates to a video loader that respects self.num_frames (default 32). The load_base64("video/jpeg", ...) path bypasses this limit entirely, data.split(",") produces an unbounded list and every frame is decoded into a numpy array.

video/jpeg is part of vLLM's public API

video/jpeg is a vLLM-specific MIME type, not IANA-registered. However it is part of the public API surface:

• encode_video_url() at vllm/multimodal/utils.py:96-108 generates data:video/jpeg;base64,... URLs
• Official test suites at tests/entrypoints/openai/test_video.py:62 and tests/entrypoints/test_chat_utils.py:153 both use this format

Memory amplification

Each JPEG frame decodes to a full numpy array. For 640x480 RGB images, each frame is ~921 KB decoded. 5000 frames = ~4.6 GB. np.stack() then creates an additional copy. The compressed JPEG payload is small (~100 KB for 5000 frames) but decompresses to gigabytes.

Data flow

POST /v1/chat/completions
  → chat_utils.py:1434   video_url type → mm_parser.parse_video()
  → chat_utils.py:872    parse_video() → self._connector.fetch_video()
  → connector.py:295     fetch_video() → load_from_url(url, self.video_io)
  → connector.py:91      _load_data_url(): url_spec.path.split(",", 1)
                          → media_type = "video/jpeg"
                          → data = "<frame1>,<frame2>,...,<frame10000>"
  → connector.py:100     media_io.load_base64("video/jpeg", data)
  → video.py:54          data.split(",")  ← UNBOUNDED
  → video.py:55-57       all frames decoded into numpy arrays
  → video.py:56          np.stack([...])  ← massive combined array → OOM

connector.py:91 uses split(",", 1) which splits on only the first comma. All remaining commas stay in data and are later split by video.py:54.

Comparison with existing protections

The application allocates resources such as memory, threads, or file descriptors based on untrusted input without enforcing a cap. Typical impact: resource exhaustion leading to denial of service.

CVE-2026-34755 has a CVSS score of 6.5 (Medium). The vector is network-reachable, low privileges required, and no user interaction. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (0.19.0); upgrading removes the vulnerable code path.

Kodem intelligence

1. What is CVE-2026-34755? CVE-2026-34755 is a medium-severity allocation of resources without limits or throttling vulnerability in vllm (pip), affecting versions >= 0.7.0, < 0.19.0. It is fixed in 0.19.0. The application allocates resources such as memory, threads, or file descriptors based on untrusted input without enforcing a cap.
2. How severe is CVE-2026-34755? CVE-2026-34755 has a CVSS score of 6.5 (Medium). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
3. Which versions of vllm are affected by CVE-2026-34755? vllm (pip) versions >= 0.7.0, < 0.19.0 is affected.
4. Is there a fix for CVE-2026-34755? Yes. CVE-2026-34755 is fixed in 0.19.0. Upgrade to this version or later.
5. Is CVE-2026-34755 exploitable, and should I be worried? Whether CVE-2026-34755 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
6. What actually determines whether CVE-2026-34755 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
7. How do I fix CVE-2026-34755? Upgrade vllm to 0.19.0 or later.