JLSEC-2026-642

A flaw was found in FFmpeg’s TensorFlow backend within the libavfilter/dnnbackendtf.c source file. The issue occurs in the dnnexecutemodeltf function, where a task object is freed multiple times in certain error-handling paths. This redundant memory deallocation can lead to a double-free conditio...

CVE-2025-71370

Vulnerability summary (CVE-2025-71370): picklescan before 0.0.28 fails to detect malicious torch.jit.unsupported_tensor_ops.execWrapper function calls embedded in pickle files. Attackers can craft malicious pickle files that bypass picklescan detection and execute arbitrary code when loaded via p...

CVE-2026-53923

vLLM is an inference and serving engine for large language models LLMs. From 0.5.5 until 0.23.1rc0, integer truncation of tensor dimensions in vLLM's GGUF dequantize kernels csrc/quantization/gguf/ggufkernel.cu causes partial tensor processing. The output tensor is allocated at full size via...

CVE-2026-53923

Summary of CVE-2026-53923 : The vulnerability affects vLLM (GGUF dequantize kernels) where integer truncation of tensor dimensions causes partially filled output tensors. From 0.5.5 up to 0.23.1rc0, the code allocates the full output tensor (torch::empty) but the CUDA kernel processes only a trun...

CVE-2026-53923 vLLM GGUF Kernels: int64_t to int truncation of tensor dimensions causes GPU buffer overflow

vLLM is an inference and serving engine for large language models LLMs. From 0.5.5 until 0.23.1rc0, integer truncation of tensor dimensions in vLLM's GGUF dequantize kernels csrc/quantization/gguf/ggufkernel.cu causes partial tensor processing. The output tensor is allocated at full size via...

CVE-2026-53923 vLLM GGUF Kernels: int64_t to int truncation of tensor dimensions causes GPU buffer overflow

vLLM is an inference and serving engine for large language models LLMs. From 0.5.5 until 0.23.1rc0, integer truncation of tensor dimensions in vLLM's GGUF dequantize kernels csrc/quantization/gguf/ggufkernel.cu causes partial tensor processing. The output tensor is allocated at full size via...

Duplicate Advisory: vLLM introduced enhanced protection for CVE-2025-62164

Duplicate Advisory This advisory has been withdrawn because it is a duplicate of GHSA-mcmc-2m55-j8jj. This link is maintained to preserve external references. Original Description vLLM versions = 0.10.2 and 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because...

PYSEC-2026-250

vLLM versions = 0.10.2 and 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed negative or out-of-bounds tensor indices, when the...

PYSEC-2026-250

vLLM versions = 0.10.2 and 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed negative or out-of-bounds tensor indices, when the...

CVE-2026-56340 vLLM - Denial of Service via Unvalidated Multimodal Embeddings

vLLM versions = 0.10.2 and 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed negative or out-of-bounds tensor indices, when the...

CVE-2026-56340 vLLM - Denial of Service via Unvalidated Multimodal Embeddings

vLLM versions = 0.10.2 and 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed negative or out-of-bounds tensor indices, when the...

CVE-2026-56340

vLLM versions = 0.10.2 and 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed negative or out-of-bounds tensor indices, when the...

CVE-2026-56340 vLLM - Denial of Service via Unvalidated Multimodal Embeddings

vLLM versions = 0.10.2 and 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed negative or out-of-bounds tensor indices, when the...

CVE-2026-56340

vLLM versions >= 0.10.2 and

PT-2026-51172

Name of the Vulnerable Software and Affected Versions vLLM versions 0.10.2 through 0.12.x Description Multimodal embeddings processing lacks sparse tensor validation. Since PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests containing...

CVE-2026-49121

A flaw was found in AI Tensor Engine for ROCm AITER. This vulnerability allows unauthenticated remote attackers to execute arbitrary code by sending a specially crafted data package, known as a pickle payload, to a ZeroMQ ZMQ subscriber socket. This exploitation is possible due to a lack of...

GHSA-X5MV-8WGW-29HG tract-nnef: integer overflow in NNEF `.dat` tensor parser yields an out-of-bounds read on model load

Component: tract-nnef nnef/src/tensors.rs::readtensor + tract-data data/src/tensor.rs - Affected versions: 0.21.16, 0.22.0–0.22.2, 0.23.0–0.23.1 — the dense DatLoader path was unguarded across all three release lines; patched in 0.21.16 / 0.22.2 / 0.23.1 - Class: CWE-190 integer overflow →...

Integer overflow in tract-nnef NNEF tensor parser leads to out-of-bounds read on model load

tractnnef::tensors::readtensor builds a tensor shape from attacker-controlled 32-bit dimensions and computes both the element count productshape and the byte allocation productshape sizeofdt with unchecked usize arithmetic. In release builds no overflow-checks both products wrap modulo 2^64. A...

PT-2026-50729

Name of the Vulnerable Software and Affected Versions tract-nnef versions prior to 0.21.16 tract-nnef versions 0.22.0 through 0.22.1 tract-nnef versions 0.23.0 Description An integer overflow exists in the read tensor function within the tract-nnef component and tract-data component. The software...

Incorrect Conversion between Numeric Types

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Incorrect Conversion between Numeric Types in the ggmldequantize, ggmlmulmatveca8, ggmlmulmata8, and ggmlmoea8 functions when tensor dimensions are...