CVE-2022-29197 – tensorflow

Package

Manager: pip
Name: tensorflow
Vulnerable Version: >=0 <2.6.4 || >=2.7.0 <2.7.2 || >=2.8.0 <2.8.1

Severity

Level: Medium

CVSS v3.1: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

CVSS v4.0: CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

EPSS: 0.00044 pctl0.12769

Details

Missing validation causes denial of service via `UnsortedSegmentJoin` ### Impact The implementation of [`tf.raw_ops.UnsortedSegmentJoin`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/unsorted_segment_join_op.cc#L92-L95) 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.raw_ops.UnsortedSegmentJoin( inputs=tf.constant("this", shape=[12], dtype=tf.string), segment_ids=tf.constant(0, shape=[12], dtype=tf.int64), num_segments=tf.constant(0, shape=[12], dtype=tf.int64)) ``` The code assumes `num_segments` is a scalar but there is no validation for this before accessing its value: ```cc const Tensor& num_segments_tensor = context->input(2); OP_REQUIRES(context, num_segments_tensor.NumElements() != 0, errors::InvalidArgument("Number of segments cannot be empty.")); auto num_segments = num_segments_tensor.scalar<NUM_SEGMENTS_TYPE>()(); ``` ### Patches We have patched the issue in GitHub commit [13d38a07ce9143e044aa737cfd7bb759d0e9b400](https://github.com/tensorflow/tensorflow/commit/13d38a07ce9143e044aa737cfd7bb759d0e9b400). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Neophytos Christou from Secure Systems Lab at Brown University.

Metadata

Created: 2022-05-24T22:08:20Z
Modified: 2022-05-24T22:08:20Z
Source: https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2022/05/GHSA-hrg5-737c-2p56/GHSA-hrg5-737c-2p56.json
CWE IDs: ["CWE-20"]
Alternative ID: GHSA-hrg5-737c-2p56
Finding: F184
Auto approve: 1