CVE-2026-22773

Users can crash the vLLM engine serving multimodal models that use the Idefics3 vision model implementation by sending a specially crafted 1x1 pixel image. This causes a tensor dimension mismatch that results in an unhandled runtime error, leading to complete server termination.

Details

The vulnerability is triggered when the image processor encounters a 1x1 pixel image with shape (1, 1, 3) in HWC (Height, Width, Channel) format. Due to the ambiguous dimensions, the processor incorrectly assumes the image is in CHW (Channel, Height, Width) format with shape (3, H, W). This misinterpretation causes an incorrect calculation of the number of image patches, resulting in a fatal tensor split operation failure.

Crash location: vllm/model_executor/models/idefics3.py line 672:

def _process_image_input(self, image_input: ImageInputs) -> torch.Tensor | list[torch.Tensor]:
    # ...
    num_patches = image_input["num_patches"]
    return [e.flatten(0, 1) for e in image_features.split(num_patches.tolist())]

The split() call fails because the computed num_patches value (17) does not match the actual tensor dimension (9):

RuntimeError: split_with_sizes expects split_sizes to sum exactly to 9 
(input tensor's size at dimension 0), but got split_sizes=[17]

This unhandled exception terminates the EngineCore process, crashing the server.

Affected Models

Any model using the Idefics3 architecture. The vulnerability was tested with HuggingFaceTB/SmolVLM-Instruct.

Mitigation

Validating the input:

def _validate_image_dimensions(self, image_shape):
    h, w = image_shape[:2] if len(image_shape) == 3 else image_shape
    if h < MIN_IMAGE_SIZE or w < MIN_IMAGE_SIZE:
        raise ValueError(f"Image dimensions too small: {h}x{w}")

Managing the exception:

try:
    return [e.flatten(0, 1) for e in image_features.split(num_patches.tolist())]
except RuntimeError as e:
    logger.error(f"Image processing failed: {e}")
    raise InvalidImageError("Failed to process image features") from e

Fixes

• https://github.com/vllm-project/vllm/pull/29881

Denial of service by crashing the engine

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-2026-22773 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 (0.12.0); upgrading removes the vulnerable code path.

Kodem intelligence

1. What is CVE-2026-22773? CVE-2026-22773 is a medium-severity allocation of resources without limits or throttling vulnerability in vllm (pip), affecting versions >= 0.6.4, < 0.12.0. It is fixed in 0.12.0. The application allocates resources such as memory, threads, or file descriptors based on untrusted input without enforcing a cap.
2. How severe is CVE-2026-22773? CVE-2026-22773 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-2026-22773? vllm (pip) versions >= 0.6.4, < 0.12.0 is affected.
4. Is there a fix for CVE-2026-22773? Yes. CVE-2026-22773 is fixed in 0.12.0. Upgrade to this version or later.
5. Is CVE-2026-22773 exploitable, and should I be worried? Whether CVE-2026-22773 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-2026-22773 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-2026-22773? Upgrade vllm to 0.12.0 or later.