CVE-2020-15210
Description
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 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 | <1.15.4 | 1.15.4 |
| PyPI | tensorflow | >=2.0.0,<2.0.3 | 2.0.3 |
| PyPI | tensorflow | >=2.1.0,<2.1.2 | 2.1.2 |
| PyPI | tensorflow | >=2.2.0,<2.2.1 | 2.2.1 |
| 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 | >=2.1.0,<2.1.2 | 2.1.2 |
| PyPI | tensorflow-cpu | >=2.2.0,<2.2.1 | 2.2.1 |
| PyPI | tensorflow-gpu | <1.15.4 | 1.15.4 |
| 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-cpu | >=2.3.0,<2.3.1 | 2.3.1 |
| PyPI | tensorflow-gpu | >=2.3.0,<2.3.1 | 2.3.1 |
| PyPI | tensorflow | <d58c96946b2880991d63d1dacacb32f0a4dfa453||>=2.3.0,<2.3.1 | d58c96946b2880991d63d1dacacb32f0a4dfa453 |
| PyPI | tensorflow-cpu | <d58c96946b2880991d63d1dacacb32f0a4dfa453||>=2.3.0,<2.3.1 | d58c96946b2880991d63d1dacacb32f0a4dfa453 |
| PyPI | tensorflow-gpu | <d58c96946b2880991d63d1dacacb32f0a4dfa453||>=2.3.0,<2.3.1 | d58c96946b2880991d63d1dacacb32f0a4dfa453 |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x9j7-x98r-r4w2
- https://nvd.nist.gov/vuln/detail/CVE-2020-15210
- https://github.com/tensorflow/tensorflow/commit/094329d0dcb8290bed2b1ee420934971f422c86d
- https://github.com/tensorflow/tensorflow/commit/1c8709b437fec10875b0cf271889afec9bbf582e
- https://github.com/tensorflow/tensorflow/commit/8c2092e9f9ef78b3f9060f8bf5ce7a49d1ccdc8f
- https://github.com/tensorflow/tensorflow/commit/d58c96946b2880991d63d1dacacb32f0a4dfa453
- https://github.com/tensorflow/tensorflow/commit/f4159ccef23d11eb58ee4263beaaeac1be3343c7
- https://github.com/tensorflow/tensorflow/commit/f50a14b00560a383865c2273e4a9094add3888d5
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-290.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-325.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-133.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-2020-15210
Community-verified mitigations for this CVE will appear above when contributors publish them.
Verify integrity in audit chain (admin only). AS-IS.