CVE-2020-15212
Description
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `output_data` buffer. This might result in a segmentation fault but it can also be used to further corrupt the memory and can be chained with other vulnerabilities to create more advanced exploits. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are all positive, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.
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.
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OS impact
Debian Fixed 2 releases
| Version | Status | Fixed in |
|---|---|---|
| sid | Fixed | 0 |
| forky | Fixed | 0 |
Package impact
| Ecosystem | Package | Vulnerable | Fixed |
|---|---|---|---|
| PyPI | tensorflow | >=2.2.0,<2.2.1 | 2.2.1 |
| PyPI | tensorflow | >=2.3.0,<2.3.1 | 2.3.1 |
| 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 | >=2.2.0,<2.2.1 | 2.2.1 |
| PyPI | tensorflow-gpu | >=2.3.0,<2.3.1 | 2.3.1 |
| PyPI | tensorflow-gpu | <204945b19e44b57906c9344c0d00120eeeae178a||>=2.2.0,<2.2.1 | 204945b19e44b57906c9344c0d00120eeeae178a |
| PyPI | tensorflow | <204945b19e44b57906c9344c0d00120eeeae178a||>=2.2.0,<2.2.1 | 204945b19e44b57906c9344c0d00120eeeae178a |
| PyPI | tensorflow-cpu | <204945b19e44b57906c9344c0d00120eeeae178a||>=2.2.0,<2.2.1 | 204945b19e44b57906c9344c0d00120eeeae178a |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx2x-85gr-wrpq
- https://nvd.nist.gov/vuln/detail/CVE-2020-15212
- https://github.com/tensorflow/tensorflow/commit/00c7ed7ce81c2126ebc17dfe7073b5c0efd5ec0a
- https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a
- https://github.com/tensorflow/tensorflow/commit/a4030d8ba3692c438997c27be2dd95f3d5f54827
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-292.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-327.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-135.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reference_ops.h#L2625-L2631
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://security-tracker.debian.org/tracker/CVE-2020-15212
Community-verified mitigations for this CVE will appear above when contributors publish them.
Verify integrity in audit chain (admin only). AS-IS.