Allocation of Resources Without Limits or Throttling

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling in the request.file.read process. An attacker can exhaust system memory or cause process...

PYSEC-2026-2303

vLLM is a library for LLM inference and serving. From 0.12.0 to before 0.24.0, sending a pure prompt embeds payload in a /v1/completions request with a model using M-RoPE causes EngineCore to fail an assertion and fatally crash, shutting down the entire server application. Any remote user who is...

PYSEC-2026-2303

vLLM is a library for LLM inference and serving. From 0.12.0 to before 0.24.0, sending a pure prompt embeds payload in a /v1/completions request with a model using M-RoPE causes EngineCore to fail an assertion and fatally crash, shutting down the entire server application. Any remote user who is...

CVE-2026-55514

CVE-2026-55514 affects the vLLM library (inference/serving) from versions 0.12.0 through older than 0.24.0. Sending a pure prompt embeds payload in a /v1/completions request for a model using M-RoPE triggers an EngineCore assertion, causing a fatal crash that shuts down the entire server applicat...

Interpretation Conflict

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Interpretation Conflict in the image processing pipeline. An attacker can cause the model to interpret images differently from human expectations by...

CVE-2026-12491 Vllm: vllm: image exif rotation & png trns transparency not normalized, causing mismatch between model input and expectations

A flaw was found in vLLM, an open-source library for large language model inference. This vulnerability arises from improper handling of image metadata, specifically EXIF orientation and PNG transparency tRNS data, during image processing. When images are converted to RGB, transparency informatio...

PT-2026-50278

Name of the Vulnerable Software and Affected Versions vLLM affected versions not specified Description An issue exists in the image processing logic where image metadata is improperly handled. Specifically, the software fails to call ImageOps.exif transpose to normalize EXIF orientation, causing...

The vulnerability of the MultiModalHasher class in the library for working with Large Language Models (LLMs) allows a hacker to disclose protected information.

The vulnerability of the MultiModalHasher class in the library for working with Large Language Models LLMs vLLM is related to improper verification of consistency in input data. Exploiting this vulnerability can allow a remote attacker to disclose sensitive information that is protected by this...

The vulnerability of the vLLM library for working with large language models involves unverified array indexing, which allows attackers to trigger service interruptions.

The vulnerability of the vLLM library for working with large language models is related to unverified array indexing. Exploiting this vulnerability could allow a malicious actor to cause service failures...

The vulnerability of the vLLM library for working with large language models, related to unlimited resource distribution, allows a hacker to trigger a service failure.

The vulnerability of the vLLM library for working with large language models is related to the unlimited distribution of resources during the processing of the chattemplatekwargs parameter. Exploiting this vulnerability could allow a malicious actor to cause service failures...

The vulnerability of the Completions API component in the LLM library vLLM allows a attacker to trigger a service failure and execute arbitrary code.

The vulnerability of the Completions API component in the vLLM language model processing library is related to writing beyond the buffer boundaries in memory. Exploiting this vulnerability could allow an attacker to trigger a service failure and execute arbitrary code...

The vulnerability in the AuthenticationMiddleware class of the vLLM library allows attackers to bypass security restrictions and disclose sensitive information.

The vulnerability of the AuthenticationMiddleware class in the library for working with Large Language Models LLMs like vLLM is related to the use of hidden time channels for data transmission. Exploiting this vulnerability can allow an attacker to bypass security restrictions and disclose...

EUVD-2025-0192

Malicious code in bioql PyPI...

EUVD-2024-2882

Malicious code in bioql PyPI...

The vulnerability of the v1/completions interface of the LLM vLLM library allows a attacker to trigger a service failure.

The vulnerability of the v1/completions interface of the LLM library for working with large language models is related to an error in handling exceptional states. Exploiting this vulnerability could allow a malicious actor to cause service failures...

CVE-2025-24357

vLLM is a library for LLM inference and serving. vllm/modelexecutor/weightutils.py implements hfmodelweightsiterator to load the model checkpoint, which is downloaded from huggingface. It uses the torch.load function and the weightsonly parameter defaults to False. When torch.load loads malicious...

PYSEC-2025-58

vLLM is a library for LLM inference and serving. vllm/modelexecutor/weightutils.py implements hfmodelweightsiterator to load the model checkpoint, which is downloaded from huggingface. It uses the torch.load function and the weightsonly parameter defaults to False. When torch.load loads malicious...

CVE-2025-24357

The CVE-2025-24357 issue centers on vLLM’s hf_model_weights_iterator (vllm/model_executor/weight_utils.py) which loads checkpoints via torch.load with weights_only defaulting to False. If malicious pickle data is unpickled, arbitrary code could execute on the host. This vulnerability is highlight...

CVE-2025-24357 vLLM allows a malicious model RCE by torch.load in hf_model_weights_iterator

vLLM is a library for LLM inference and serving. vllm/modelexecutor/weightutils.py implements hfmodelweightsiterator to load the model checkpoint, which is downloaded from huggingface. It uses the torch.load function and the weightsonly parameter defaults to False. When torch.load loads malicious...

GHSA-W2R7-9579-27HF vLLM denial of service vulnerability

A flaw was found in the vLLM library. A completions API request with an empty prompt will crash the vLLM API server, resulting in a denial of service...