PT-2026-59784

Impact The macros that TensorFlow uses for writing assertions e.g., CHECK LT, CHECK GT, etc. have an incorrect logic when comparing size t and int values. Due to type conversion rules, several of the macros would trigger incorrectly. Patches We have patched the issue in GitHub commit...

PT-2026-59868

Impact In multiple places, TensorFlow uses tempfile.mktemp to create temporary files. While this is acceptable in testing, in utilities and libraries it is dangerous as a different process can create the file between the check for the filename in mktemp and the actual creation of the file by a...

PT-2026-59768

Impact An attacker can craft a TFLite model that would cause an integer overflow in TfLiteIntArrayCreate: cc TfLiteIntArray TfLiteIntArrayCreateint size int alloc size = TfLiteIntArrayGetSizeInBytessize; // ... TfLiteIntArray ret = TfLiteIntArraymallocalloc size; // ... The...

PT-2026-59929

Impact The macros that TensorFlow uses for writing assertions e.g., CHECK LT, CHECK GT, etc. have an incorrect logic when comparing size t and int values. Due to type conversion rules, several of the macros would trigger incorrectly. Patches We have patched the issue in GitHub commit...

PT-2026-59973

Impact The GatherNd function takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read is triggered. Patches We have patched the issue in GitHub commit...

PT-2026-59776

Impact The implementation of shape inference for Dequantize is vulnerable to an integer overflow weakness: python import tensorflow as tf input = tf.constant1,1,dtype=tf.qint32 @tf.function def test: y = tf.raw ops.Dequantize input=input, min range=1.0, max range=10.0, mode='MIN COMBINED', narrow...

PT-2026-59711

Impact When Conv2DBackpropInput receives empty out backprop inputs e.g. 3, 1, 0, 1, the current CPU/GPU kernels CHECK fail one with dnnl, the other with cudnn. This can be used to trigger a denial of service attack. python import tensorflow as tf import numpy as np input sizes = 3, 1, 1, 2 filter...

PT-2026-59956

Impact The implementation of tf.raw ops.UnsortedSegmentJoin does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack: python import tensorflow as tf tf.strings.unsorted segment join inputs='123', segment ids=0, num...

cogdata (>=0.0.6, <=0.0.7), icetk (>=0.0.5, <=0.0.7) +3 more potentially affected by CVE-2026-0994 via protobuf (3.19.0rc2)

protobuf PYPI version 3.19.0rc2 is affected by a known vulnerability. The following packages have a transitive dependency on protobuf and may be impacted: - cogdata =0.0.6, =0.0.5, =3.0.0a2, =4.7.2 - motion-master-proto 5.2.0 - tensorflow-checkpoint-reader 0.1.2 Source cves: CVE-2026-0994 Source...

hydra-rbp (>=0.1.21.29, <=0.1.21.38), phasespace (>=1.5.0, <=1.6.0) +4 more potentially affected by CVE-2025-12060 via keras (2.7.0rc2)

keras PYPI version 2.7.0rc2 is affected by a known vulnerability. The following packages have a transitive dependency on keras and may be impacted: - hydra-rbp =0.1.21.29, =1.5.0, =2.6.0rc1, =0.18.0.dev20210402154254, =0.3.0, =0.3.2 Source cves: CVE-2025-12060 Source advisory: OSV:PYSEC-2026-1486...

tensorflow (2.6.0rc0) potentially affected by CVE-2025-12060 via keras (2.6.0rc0)

keras PYPI version 2.6.0rc0 is affected by a known vulnerability. The following packages have a transitive dependency on keras and may be impacted: - tensorflow 2.6.0rc0 Source cves: CVE-2025-12060 Source advisory: OSV:PYSEC-2026-1486...

Hugging Face Transformers Regular Expression Denial of Service (ReDoS) vulnerability

A Regular Expression Denial of Service ReDoS vulnerability exists in the Hugging Face Transformers library, specifically in the converttfweightnametoptweightname function. This function, responsible for converting TensorFlow weight names to PyTorch format, uses a regex pattern /^/^// that can be...

cogdata (>=0.0.6, <=0.0.7), icetk (>=0.0.5, <=0.0.7) +3 more potentially affected by CVE-2025-4565 via protobuf (3.19.0rc2)

protobuf PYPI version 3.19.0rc2 is affected by a known vulnerability. The following packages have a transitive dependency on protobuf and may be impacted: - cogdata =0.0.6, =0.0.5, =3.0.0a2, =4.7.2 - motion-master-proto 5.2.0 - tensorflow-checkpoint-reader 0.1.2 Source cves: CVE-2025-4565 Source...

PYSEC-2026-1962 TensorFlow has segfault in array_ops.upper_bound

Impact arrayops.upperbound causes a segfault when not given a rank 2 tensor. Patches We have patched the issue in GitHub commit 915884fdf5df34aaedd00fc6ace33a2cfdefa586. The fix will be included in TensorFlow 2.13. We will also cherrypick this commit in TensorFlow 2.12.1. For more information...

TensorFlow has segfault in array_ops.upper_bound

Impactarrayops.upperbound causes a segfault when not given a rank 2 tensor. PatchesWe have patched the issue in GitHub commit 915884fdf5df34aaedd00fc6ace33a2cfdefa586.The fix will be included in TensorFlow 2.13. We will also cherrypick this commit in TensorFlow 2.12.1. For more informationPlease...

Invalid char to bool conversion when printing a tensor

ImpactWhen printing a tensor, we get it's data as a const char array since that's the underlying storage and then we typecast it to the element type. However, conversions from char to bool are undefined if the char is not 0 or 1, so sanitizers/fuzzers will crash. PatchesWe have patched the issue ...

PYSEC-2026-1954 Invalid char to bool conversion when printing a tensor

Impact When printing a tensor, we get it's data as a const char array since that's the underlying storage and then we typecast it to the element type. However, conversions from char to bool are undefined if the char is not 0 or 1, so sanitizers/fuzzers will crash. Patches We have patched the issu...

PYSEC-2026-1654 MLFlow unsafe deserialization

Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.0.0rc0 or newer, enabling a maliciously uploaded Tensorflow model to run arbitrary code on an end user’s system when interacted with...

MLFlow unsafe deserialization

Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.0.0rc0 or newer, enabling a maliciously uploaded Tensorflow model to run arbitrary code on an end user’s system when interacted with...

Authenticated Local Privilege Escalation vulnerability in Intel Optimization for Tensorflow

Improper buffer restrictions in the IntelR Optimization for Tensorflow software before version 2.12 may allow an authenticated user to potentially enable escalation of privilege via local access...