| CVE-ID | ||
|---|---|---|
CVE-2021-37654 |
• CVSS Severity Rating • Fix Information • Vulnerable Software Versions • SCAP Mappings • CPE Information
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| Description | ||
| TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a crash via a `CHECK`-fail in debug builds of TensorFlow using `tf.raw_ops.ResourceGather` or a read from outside the bounds of heap allocated data in the same API in a release build. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L660-L668) does not check that the `batch_dims` value that the user supplies is less than the rank of the input tensor. Since the implementation uses several for loops over the dimensions of `tensor`, this results in reading data from outside the bounds of heap allocated buffer backing the tensor. We have patched the issue in GitHub commit bc9c546ce7015c57c2f15c168b3d9201de679a1d. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | ||
| References | ||
| Note: References are provided for the convenience of the reader to help distinguish between vulnerabilities. The list is not intended to be complete. | ||
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| Assigning CNA | ||
| GitHub (maintainer security advisories) | ||
| Date Record Created | ||
| 20210729 | Disclaimer: The record creation date may reflect when the CVE ID was allocated or reserved, and does not necessarily indicate when this vulnerability was discovered, shared with the affected vendor, publicly disclosed, or updated in CVE. | |
| Phase (Legacy) | ||
| Assigned (20210729) | ||
| Votes (Legacy) | ||
| Comments (Legacy) | ||
| Proposed (Legacy) | ||
| N/A | ||
| This is an record on the CVE List, which provides common identifiers for publicly known cybersecurity vulnerabilities. | ||
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