CVE-2021-29549
Description
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) computes a modulo operation without validating that the divisor is not zero. Since `vector_num_elements` is determined based on input shapes(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L522-L544), a user can trigger scenarios where this quantity is 0. 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.
The vendor-content worker queues fetches as references arrive (check back in a few minutes). Or — if you've already worked around this in production — publish your fix to the community-verified tier.
✚ Propose a mitigation on Community → Mitigations published via the community go through AI scoring + 2 human reviewers + 7-day silent objection window before landing here withsource_tier=community-verified.
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 | <2.1.4 | 2.1.4 |
| PyPI | tensorflow | >=2.2.0,<2.2.3 | 2.2.3 |
| PyPI | tensorflow | >=2.3.0,<2.3.3 | 2.3.3 |
| PyPI | tensorflow | >=2.4.0,<2.4.2 | 2.4.2 |
| PyPI | tensorflow-cpu | <2.1.4 | 2.1.4 |
| PyPI | tensorflow-cpu | >=2.2.0,<2.2.3 | 2.2.3 |
| PyPI | tensorflow-cpu | >=2.3.0,<2.3.3 | 2.3.3 |
| PyPI | tensorflow-cpu | >=2.4.0,<2.4.2 | 2.4.2 |
| PyPI | tensorflow-gpu | <2.1.4 | 2.1.4 |
| PyPI | tensorflow-gpu | >=2.2.0,<2.2.3 | 2.2.3 |
| PyPI | tensorflow-gpu | >=2.3.0,<2.3.3 | 2.3.3 |
| PyPI | tensorflow-gpu | >=2.4.0,<2.4.2 | 2.4.2 |
| PyPI | tensorflow | <744009c9e5cc5d0447f0dc39d055f917e1fd9e16||>=2.4.0,<2.4.3 | 744009c9e5cc5d0447f0dc39d055f917e1fd9e16 |
| PyPI | tensorflow-cpu | <744009c9e5cc5d0447f0dc39d055f917e1fd9e16||>=2.4.0,<2.4.3 | 744009c9e5cc5d0447f0dc39d055f917e1fd9e16 |
| PyPI | tensorflow-gpu | <744009c9e5cc5d0447f0dc39d055f917e1fd9e16||>=2.4.0,<2.4.3 | 744009c9e5cc5d0447f0dc39d055f917e1fd9e16 |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8v
- https://nvd.nist.gov/vuln/detail/CVE-2021-29549
- https://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-477.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-675.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-186.yaml
- https://github.com/tensorflow/tensorflow
- https://security-tracker.debian.org/tracker/CVE-2021-29549
Community-verified mitigations for this CVE will appear above when contributors publish them.
Verify integrity in audit chain (admin only). AS-IS.