Ecosyste.ms: Advisories
An open API service providing security vulnerability metadata for many open source software ecosystems.
Security Advisories: GSA_kwCzR0hTQS0ycjJmLWc4bXctOWd2cs4AArBU
Segfault and OOB write due to incomplete validation in `EditDistance` in TensorFlow
Impact
The implementation of tf.raw_ops.EditDistance
has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service:
import tensorflow as tf
hypothesis_indices = tf.constant(-1250999896764, shape=[3, 3], dtype=tf.int64)
hypothesis_values = tf.constant(0, shape=[3], dtype=tf.int64)
hypothesis_shape = tf.constant(0, shape=[3], dtype=tf.int64)
truth_indices = tf.constant(-1250999896764, shape=[3, 3], dtype=tf.int64)
truth_values = tf.constant(2, shape=[3], dtype=tf.int64)
truth_shape = tf.constant(2, shape=[3], dtype=tf.int64)
tf.raw_ops.EditDistance(
hypothesis_indices=hypothesis_indices,
hypothesis_values=hypothesis_values,
hypothesis_shape=hypothesis_shape,
truth_indices=truth_indices,
truth_values=truth_values,
truth_shape=truth_shape)
In multiple places throughout the code, we are computing an index for a write operation:
if (g_truth == g_hypothesis) {
auto loc = std::inner_product(g_truth.begin(), g_truth.end(),
output_strides.begin(), int64_t{0});
OP_REQUIRES(
ctx, loc < output_elements,
errors::Internal("Got an inner product ", loc,
" which would require in writing to outside of "
"the buffer for the output tensor (max elements ",
output_elements, ")"));
output_t(loc) =
gtl::LevenshteinDistance<T>(truth_seq, hypothesis_seq, cmp);
// ...
}
However, the existing validation only checks against the upper bound of the array. Hence, it is possible to write before the array by massaging the input to generate negative values for loc
.
Patches
We have patched the issue in GitHub commit 30721cf564cb029d34535446d6a5a6357bebc8e7.
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 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.
Permalink: https://github.com/advisories/GHSA-2r2f-g8mw-9gvrJSON: https://advisories.ecosyste.ms/api/v1/advisories/GSA_kwCzR0hTQS0ycjJmLWc4bXctOWd2cs4AArBU
Source: GitHub Advisory Database
Origin: Unspecified
Severity: High
Classification: General
Published: almost 2 years ago
Updated: about 1 year ago
CVSS Score: 7.1
CVSS vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H
Identifiers: GHSA-2r2f-g8mw-9gvr, CVE-2022-29208
References:
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2r2f-g8mw-9gvr
- https://nvd.nist.gov/vuln/detail/CVE-2022-29208
- https://github.com/tensorflow/tensorflow/commit/30721cf564cb029d34535446d6a5a6357bebc8e7
- https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4
- https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2
- https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1
- https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0
- https://github.com/advisories/GHSA-2r2f-g8mw-9gvr
Blast Radius: 34.6
Affected Packages
pypi:tensorflow-gpu
Dependent packages: 146Dependent repositories: 11,499
Downloads: 350,104 last month
Affected Version Ranges: >= 2.8.0, < 2.8.1, >= 2.7.0, < 2.7.2, < 2.6.4
Fixed in: 2.8.1, 2.7.2, 2.6.4
All affected versions: 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.7.0, 1.7.1, 1.8.0, 1.9.0, 1.10.0, 1.10.1, 1.11.0, 1.12.0, 1.12.2, 1.12.3, 1.13.1, 1.13.2, 1.14.0, 1.15.0, 1.15.2, 1.15.3, 1.15.4, 1.15.5, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.7.0, 2.7.1, 2.8.0
All unaffected versions: 2.6.4, 2.6.5, 2.7.2, 2.7.3, 2.7.4, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.12.0
pypi:tensorflow-cpu
Dependent packages: 71Dependent repositories: 2,483
Downloads: 940,986 last month
Affected Version Ranges: >= 2.8.0, < 2.8.1, >= 2.7.0, < 2.7.2, < 2.6.4
Fixed in: 2.8.1, 2.7.2, 2.6.4
All affected versions: 1.15.0, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.7.0, 2.7.1, 2.8.0
All unaffected versions: 2.6.4, 2.6.5, 2.7.2, 2.7.3, 2.7.4, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.11.1, 2.12.0, 2.12.1, 2.13.0, 2.13.1, 2.14.0, 2.14.1, 2.15.0, 2.15.1, 2.16.1
pypi:tensorflow
Dependent packages: 1,733Dependent repositories: 73,755
Downloads: 22,369,513 last month
Affected Version Ranges: >= 2.8.0, < 2.8.1, >= 2.7.0, < 2.7.2, < 2.6.4
Fixed in: 2.8.1, 2.7.2, 2.6.4
All affected versions: 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0, 1.2.0, 1.2.1, 1.3.0, 1.4.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.7.0, 1.7.1, 1.8.0, 1.9.0, 1.10.0, 1.10.1, 1.11.0, 1.12.0, 1.12.2, 1.12.3, 1.13.1, 1.13.2, 1.14.0, 1.15.0, 1.15.2, 1.15.3, 1.15.4, 1.15.5, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.7.0, 2.7.1, 2.8.0
All unaffected versions: 2.6.4, 2.6.5, 2.7.2, 2.7.3, 2.7.4, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.11.1, 2.12.0, 2.12.1, 2.13.0, 2.13.1, 2.14.0, 2.14.1, 2.15.0, 2.15.1, 2.16.1