756 matches found
CVE-2026-73555
A flaw was found in vLLM, an inference and serving engine for large language models. Unauthenticated attackers can send malformed JSON requests to various API endpoints, triggering validation errors. The system's error handling mechanism converts these validation errors into strings without...
CVE-2026-73557
A flaw was found in vLLM, an inference and serving engine for large language models. An incomplete remediation for a previous vulnerability CVE-2025-62164 can be bypassed. This occurs when concurrent prompt parts are processed, leading to a race condition in the handling of sparse tensors. This...
CVE-2026-73558
A flaw was found in vLLM, an inference and serving engine for large language models. An integer overflow vulnerability in the actandmulkernel kernel allows a remote attacker to cause cross-user data leakage. By crafting specific requests processed in the same inference batch, an attacker can obta...
CVE-2026-73559
A flaw was found in vLLM, an inference and serving engine for large language models. An authenticated API client can exploit this vulnerability by sending a single request to the /v1/completions endpoint with an excessively large list of prompts. This unbounded input causes the vLLM server to...
CVE-2026-73556
A flaw was found in vLLM, an inference and serving engine for large language models. An unauthenticated remote attacker can exploit a Regular Expression Denial of Service ReDoS vulnerability in the lm-format-enforcer backend. By submitting a specially crafted regular expression through the...
vLLM: Completion prompt lists fan out into unbounded engine requests
Summary The /v1/completions request model accepts prompt as a list of text prompts or a list of token-id prompts without any outer prompt-count bound. The serving path turns each element into a separate engine input, creates one engine generator per element, merges all generators, and allocates a...
GHSA-87X5-VMC3-756J vLLM: Completion prompt lists fan out into unbounded engine requests
Summary The /v1/completions request model accepts prompt as a list of text prompts or a list of token-id prompts without any outer prompt-count bound. The serving path turns each element into a separate engine input, creates one engine generator per element, merges all generators, and allocates a...
CVE-2026-73559
vLLM is an inference and serving engine for large language models. From 0.19.0 until 0.26.0, the /v1/completions CompletionRequest.prompt field in vllm/entrypoints/openai/completion/protocol.py accepts an unbounded liststr or listlistint, prompttoseq in vllm/renderers/inputs/preprocess.py and...
CVE-2026-73558
vLLM is an inference and serving engine for large language models. Prior to 0.27.0, an integer overflow in blockIdx.x 2 d in activationkernels.cu can cause actandmulkernel to consume another batched user's input, allowing a request processed in the same inference batch to receive a partial or...
CVE-2026-73557
vLLM is an inference and serving engine for large language models. From 0.20.2rc0 until 0.26.0, safeloadpromptembeds in vllm/renderers/embedutils.py uses torch.sparse.checksparsetensorinvariants, whose process-global save, enable, and restore state can be raced by concurrent promptembeds parts...
CVE-2026-73555
vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the validationexceptionhandler in vllm/entrypoints/openai/serverutils.py converts FastAPI RequestValidationError objects with strexc, and sanitizemessage in vllm/entrypoints/utils.py does not remove traceback-styl...
CVE-2026-73556
vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the structuredoutputs.regex parameter in vllm/v1/structuredoutput/backendlmformatenforcer.py is passed to lmformatenforcer.RegexParser without compileregexwithtimeout or validation in...
CVE-2026-73559 vLLM: Completion prompt lists fan out into unbounded engine requests
vLLM is an inference and serving engine for large language models. From 0.19.0 until 0.26.0, the /v1/completions CompletionRequest.prompt field in vllm/entrypoints/openai/completion/protocol.py accepts an unbounded liststr or listlistint, prompttoseq in vllm/renderers/inputs/preprocess.py and...
CVE-2026-73559
CVE-2026-73559 affects vLLM (0.19.0–0.26.0) where the /v1/completions prompt field can be an unbounded list, and prompt_to_seq/remove expansion in preprocessing may spawn unbounded expansion and create one engine generator/response slot per prompt. This can exhaust CPU, memory, async scheduling c...
CVE-2026-73559
vLLM is an inference and serving engine for large language models. From 0.19.0 until 0.26.0, the /v1/completions CompletionRequest.prompt field in vllm/entrypoints/openai/completion/protocol.py accepts an unbounded liststr or listlistint, prompttoseq in vllm/renderers/inputs/preprocess.py and...
EUVD-2026-58067
vLLM is an inference and serving engine for large language models. From 0.19.0 until 0.26.0, the /v1/completions CompletionRequest.prompt field in vllm/entrypoints/openai/completion/protocol.py accepts an unbounded liststr or listlistint, prompttoseq in vllm/renderers/inputs/preprocess.py and...
CVE-2026-73559 vLLM: Completion prompt lists fan out into unbounded engine requests
vLLM is an inference and serving engine for large language models. From 0.19.0 until 0.26.0, the /v1/completions CompletionRequest.prompt field in vllm/entrypoints/openai/completion/protocol.py accepts an unbounded liststr or listlistint, prompttoseq in vllm/renderers/inputs/preprocess.py and...
CVE-2026-73558
The CVE concerns vLLM, an inference/serving engine for LLMs. Before version 0.27.0, an integer overflow in blockIdx.x * 2 * d within activation_kernels.cu enables act_and_mul_kernel to consume input from another user within the same inference batch, causing cross-user data leakage of partial or c...
CVE-2026-73558 vLLM: Cross-User Data Leak Vulnerability
vLLM is an inference and serving engine for large language models. Prior to 0.27.0, an integer overflow in blockIdx.x 2 d in activationkernels.cu can cause actandmulkernel to consume another batched user's input, allowing a request processed in the same inference batch to receive a partial or...
CVE-2026-73558
vLLM is an inference and serving engine for large language models. Prior to 0.27.0, an integer overflow in blockIdx.x 2 d in activationkernels.cu can cause actandmulkernel to consume another batched user's input, allowing a request processed in the same inference batch to receive a partial or...