PT-2022-16108 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.8.0 TensorFlow versions 2.7.1 and earlier TensorFlow versions 2.6.3 and earlier TensorFlow versions 2.5.3 and earlier Description: The GraphDef format in TensorFlow does not allow self recursive functions...

PT-2021-18337 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.5.0 TensorFlow versions 2.4.2 and earlier TensorFlow versions 2.3.3 and earlier TensorFlow versions 2.2.3 and earlier TensorFlow versions 2.1.4 and earlier Description: Optimized pooling implementations in TFLit...

PT-2021-18325 · Google · Tensorflow

Name of the Vulnerable Software and Affected Versions: TensorFlow versions prior to 2.5.0 TensorFlow versions 2.4.2 and earlier TensorFlow versions 2.3.3 and earlier TensorFlow versions 2.2.3 and earlier TensorFlow versions 2.1.4 and earlier Description: The implementation of tf.raw...

Segmentation fault in tensorflow-lite

Impact If a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. Patches We have patched the issue in d58c96946b and will release patch releases for all versions between 1.1...

Segfault and data corruption in tensorflow-lite

Impact To mimic Python's indexing with negative values, TFLite uses ResolveAxis to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds:...

GHSA-X5CP-9PCF-PP3H Denial of Service in Tensorflow

Impact The RaggedCountSparseOutput does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the splits tensor has the minimum required number of elements. Code uses this quantity to initialize a different data structure:...

GHSA-JC87-6VPP-7FF3 Heap buffer overflow in Tensorflow

Impact The SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel:...