CVE-2020-15190
Description
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `tf.raw_ops.Switch` operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is `nullptr`, hence we are binding a reference to `nullptr`. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
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
Debian Fixed 2 releases
| Version | Status | Fixed in |
|---|---|---|
| sid | Fixed | 0 |
| forky | Fixed | 0 |
Package impact
| Ecosystem | Package | Vulnerable | Fixed |
|---|---|---|---|
| PyPI | tensorflow | >=2.3.0,<2.3.1 | 2.3.1 |
| PyPI | tensorflow-cpu | <1.15.4 | 1.15.4 |
| PyPI | tensorflow-cpu | >=2.0.0,<2.0.3 | 2.0.3 |
| PyPI | tensorflow-cpu | >=2.2.0,<2.2.1 | 2.2.1 |
| PyPI | tensorflow-cpu | >=2.3.0,<2.3.1 | 2.3.1 |
| PyPI | tensorflow-gpu | <1.15.4 | 1.15.4 |
| PyPI | tensorflow | <1.15.4 | 1.15.4 |
| PyPI | tensorflow-gpu | >=2.3.0,<2.3.1 | 2.3.1 |
| PyPI | tensorflow-cpu | >=2.1.0,<2.1.2 | 2.1.2 |
| PyPI | tensorflow-gpu | >=2.0.0,<2.0.3 | 2.0.3 |
| PyPI | tensorflow-gpu | >=2.1.0,<2.1.2 | 2.1.2 |
| PyPI | tensorflow-gpu | >=2.2.0,<2.2.1 | 2.2.1 |
| PyPI | tensorflow | >=2.2.0,<2.2.1 | 2.2.1 |
| PyPI | tensorflow | >=2.0.0,<2.0.3 | 2.0.3 |
| PyPI | tensorflow | >=2.1.0,<2.1.2 | 2.1.2 |
| PyPI | tensorflow | <da8558533d925694483d2c136a9220d6d49d843c||>=2.3.0,<2.3.1 | da8558533d925694483d2c136a9220d6d49d843c |
| PyPI | tensorflow-cpu | <da8558533d925694483d2c136a9220d6d49d843c||>=2.3.0,<2.3.1 | da8558533d925694483d2c136a9220d6d49d843c |
| PyPI | tensorflow-gpu | <da8558533d925694483d2c136a9220d6d49d843c||>=2.3.0,<2.3.1 | da8558533d925694483d2c136a9220d6d49d843c |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4g9f-63rx-5cw4
- https://nvd.nist.gov/vuln/detail/CVE-2020-15190
- https://github.com/tensorflow/tensorflow/commit/da8558533d925694483d2c136a9220d6d49d843c
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-270.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-305.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-113.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
- https://security-tracker.debian.org/tracker/CVE-2020-15190
Community-verified mitigations for this CVE will appear above when contributors publish them.
Verify integrity in audit chain (admin only). AS-IS.