CVE-2021-29569
Description
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, `.flat<T>()` is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Predictions
Heuristic predictions, AS-IS, for prioritization only.
Mitigations
No mitigations published for this CVE yet.
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OS impact
Arch Fixed 1 release
| Version | Status | Fixed in |
|---|---|---|
| — | Fixed | 2.5.0-1 |
Debian Fixed 2 releases
| Version | Status | Fixed in |
|---|---|---|
| sid | Fixed | 0 |
| forky | Fixed | 0 |
Package impact
| Ecosystem | Package | Vulnerable | Fixed |
|---|---|---|---|
| PyPI | tensorflow-cpu | >=2.2.0,<2.2.3 | 2.2.3 |
| PyPI | tensorflow-gpu | >=2.3.0,<2.3.3 | 2.3.3 |
| PyPI | tensorflow-cpu | <2.1.4 | 2.1.4 |
| PyPI | tensorflow | >=2.2.0,<2.2.3 | 2.2.3 |
| PyPI | tensorflow-gpu | >=2.4.0,<2.4.2 | 2.4.2 |
| PyPI | tensorflow | >=2.4.0,<2.4.2 | 2.4.2 |
| PyPI | tensorflow | <2.1.4 | 2.1.4 |
| PyPI | tensorflow-cpu | >=2.4.0,<2.4.2 | 2.4.2 |
| PyPI | tensorflow-gpu | <2.1.4 | 2.1.4 |
| PyPI | tensorflow | >=2.3.0,<2.3.3 | 2.3.3 |
| PyPI | tensorflow-cpu | >=2.3.0,<2.3.3 | 2.3.3 |
| PyPI | tensorflow-gpu | >=2.2.0,<2.2.3 | 2.2.3 |
| PyPI | tensorflow | <ef0c008ee84bad91ec6725ddc42091e19a30cf0e||>=2.4.0,<2.4.2 | ef0c008ee84bad91ec6725ddc42091e19a30cf0e |
| PyPI | tensorflow-cpu | <ef0c008ee84bad91ec6725ddc42091e19a30cf0e||>=2.4.0,<2.4.2 | ef0c008ee84bad91ec6725ddc42091e19a30cf0e |
| PyPI | tensorflow-gpu | <ef0c008ee84bad91ec6725ddc42091e19a30cf0e||>=2.4.0,<2.4.2 | ef0c008ee84bad91ec6725ddc42091e19a30cf0e |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3h8m-483j-7xxm
- https://nvd.nist.gov/vuln/detail/CVE-2021-29569
- https://github.com/tensorflow/tensorflow/commit/ef0c008ee84bad91ec6725ddc42091e19a30cf0e
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-497.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-695.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-206.yaml
- https://github.com/tensorflow/tensorflow
- https://security-tracker.debian.org/tracker/CVE-2021-29569
Community-verified mitigations for this CVE will appear above when contributors publish them.
Verify integrity in audit chain (admin only). AS-IS.