ONNX: Heap-Buffer-Overflow READ in Gemm Version Converter Adapter via Undersized Input Shape

SummaryHeap-buffer-overflow READ 16 bytes in Gemm76::adaptgemm76 onnx/versionconverter/adapters/gemm76.h:41 when ConvertVersion processes a model with a Gemm node whose input tensors have fewer than 2 dimensions. The adapter accesses Bshape1 without checking rank. On Release builds the OOB read i...

PYSEC-2026-3263 TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

Impact The implementation of AvgPoolGrad does not fully validate the input originputshape. This results in a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "VALID" dataformat = "NHWC"...

PYSEC-2026-3083 TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

Impact The implementation of AvgPoolGrad does not fully validate the input originputshape. This results in a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "VALID" dataformat = "NHWC"...

PYSEC-2026-3257 TensorFlow vulnerable to `CHECK` failures in `AvgPool3DGrad`

Impact The implementation of AvgPool3DGradOp does not fully validate the input originputshape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf ksize = 1, 1, 1, 1, 1 strides = 1, 1, 1, 1, 1 padding ...

PYSEC-2026-3311 TensorFlow vulnerable to `CHECK` fail in `RandomPoissonV2`

Impact When RandomPoissonV2 receives large input shape and rates, it gives a CHECK fail that can trigger a denial of service attack. python import tensorflow as tf arg0=tf.random.uniformshape=4,, dtype=tf.int32, maxval=65536 arg1=tf.random.uniformshape=4, 4, 4, 4, 4, dtype=tf.float32, maxval=None...

TensorFlow vulnerable to `CHECK` fail in `DenseBincount`

ImpactDenseBincount assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack.pythonimport tensorflow as tfbinaryoutput = Trueinput =...

PYSEC-2026-3377 TensorFlow vulnerable to `CHECK` fail in `DenseBincount`

Impact DenseBincount assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf binaryoutput = True input =...

PYSEC-2026-940 TensorFlow vulnerable to `CHECK` fail in `AvgPoolGrad`

Impact The implementation of AvgPoolGrad does not fully validate the input originputshape. This results in a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf ksize = 1, 2, 2, 1 strides = 1, 2, 2, 1 padding = "VALID" dataformat = "NHWC"...

PYSEC-2026-1046 TensorFlow vulnerable to `CHECK` failures in `AvgPool3DGrad`

Impact The implementation of AvgPool3DGradOp does not fully validate the input originputshape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack: python import tensorflow as tf ksize = 1, 1, 1, 1, 1 strides = 1, 1, 1, 1, 1 padding ...

PYSEC-2026-969 TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`

Impact The implementation of FractionalAvgPoolGrad does not fully validate the input originputtensorshape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack. python import tensorflow as tf overlapping = True originputtensorshape =...

PYSEC-2026-1043 TensorFlow vulnerable to `CHECK` fail in `DenseBincount`

Impact DenseBincount assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack. python import tensorflow as tf binaryoutput = True input =...

CVE-2026-31230

A flaw was found in Adversarial Robustness Toolbox ART. This command-line argument injection vulnerability exists in its Kubeflow component due to the unsafe use of the eval function, which parses string values from --clipvalues and --inputshape arguments. A remote attacker can exploit this by...

EUVD-2026-29553

The Adversarial Robustness Toolbox ART thru 1.20.1 contains a command-line argument injection vulnerability in its Kubeflow component robustnessevaluationfgsmpytorch.py. The script uses the unsafe eval function to parse string values provided via the --clipvalues and --inputshape command-line...

CVE-2026-31230

The Adversarial Robustness Toolbox ART thru 1.20.1 contains a command-line argument injection vulnerability in its Kubeflow component robustnessevaluationfgsmpytorch.py. The script uses the unsafe eval function to parse string values provided via the --clipvalues and --inputshape command-line...

CVE-2026-31230

The Adversarial Robustness Toolbox ART thru 1.20.1 contains a command-line argument injection vulnerability in its Kubeflow component robustnessevaluationfgsmpytorch.py. The script uses the unsafe eval function to parse string values provided via the --clipvalues and --inputshape command-line...

CVE-2026-31230

The Adversarial Robustness Toolbox ART thru 1.20.1 contains a command-line argument injection vulnerability in its Kubeflow component robustnessevaluationfgsmpytorch.py. The script uses the unsafe eval function to parse string values provided via the --clipvalues and --inputshape command-line...

CVE-2026-31230

The CVE-2026-31230 vulnerability concerns the Adversarial Robustness Toolbox (ART) up to v1.20.1, specifically in its Kubeflow component (robustness_evaluation_fgsm_pytorch.py). The issue arises from using unsafe eval() to parse string values passed via --clip_values and --input_shape, enabling a...

CVE-2021-33654

When performing the initialization operation of the Split operator, if a dimension in the input shape is 0, it will cause a division by 0 exception...

CVE-2025-62372 vLLM vulnerable to DoS with incorrect shape of multimodal embedding inputs

vLLM is an inference and serving engine for large language models LLMs. From version 0.5.5 to before 0.11.1, users can crash the vLLM engine serving multimodal models by passing multimodal embedding inputs with correct ndim but incorrect shape e.g. hidden dimension is wrong, regardless of whether...

CVE-2025-62372 vLLM vulnerable to DoS with incorrect shape of multimodal embedding inputs

vLLM is an inference and serving engine for large language models LLMs. From version 0.5.5 to before 0.11.1, users can crash the vLLM engine serving multimodal models by passing multimodal embedding inputs with correct ndim but incorrect shape e.g. hidden dimension is wrong, regardless of whether...