CVE-2021-37663
Summary
| CVE | CVE-2021-37663 |
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| State | PUBLIC |
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| Assigner | [email protected] |
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| Source Priority | CVE Program / NVD first with legacy fallback |
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| Published | 2021-08-12 23:15:00 UTC |
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| Updated | 2021-08-19 14:41:00 UTC |
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| Description | TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in `tf.raw_ops.QuantizeV2`, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/quantize_op.cc#L59) has some validation but does not check that `min_range` and `max_range` both have the same non-zero number of elements. If `axis` is provided (i.e., not `-1`), then validation should check that it is a value in range for the rank of `input` tensor and then the lengths of `min_range` and `max_range` inputs match the `axis` dimension of the `input` tensor. We have patched the issue in GitHub commit 6da6620efad397c85493b8f8667b821403516708. 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. |
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NVD Known Affected Configurations (CPE 2.3)
References
| Reference | Source | Link | Tags |
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| Incomplete validation in `QuantizeV2` · Advisory · tensorflow/tensorflow · GitHub |
CONFIRM |
github.com |
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| Secure tf.raw_ops.QuantizeV2 · tensorflow/tensorflow@6da6620 · GitHub |
MISC |
github.com |
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| CVE Program record |
CVE.ORG |
www.cve.org |
canonical |
| NVD vulnerability detail |
NVD |
nvd.nist.gov |
canonical, analysis |
No vendor comments have been submitted for this CVE.
Legacy QID Mappings
- 981532 Python (pip) Security Update for tensorflow-gpu (GHSA-g25h-jr74-qp5j)
