Denial of Service in Tensorflow
High9.0CVE-2020-15206 · Published Sep 25, 2020 · updated Jul 8, 2026
### Impact Changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. We have added fixes to this in f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. ### Patches We have patched the issue in adf095206f25471e864a8e63a0f1caef53a0e3a6 and will release patch releases for all versions between 1.15 and 2.3. Patch releases for versions between 1.15 and 2.1 will also contain cherry-picks of f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and ques...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 1.15.4 | 1.15.4 |
| >= 2.0.0, < 2.0.3 | 2.0.3 | |
| >= 2.1.0, < 2.1.2 | 2.1.2 | |
| >= 2.2.0, < 2.2.1 | 2.2.1 | |
| >= 2.3.0, < 2.3.1 | 2.3.1 |
Details and references
### Impact Changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. We have added fixes to this in f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. ### Patches We have patched the issue in adf095206f25471e864a8e63a0f1caef53a0e3a6 and will release patch releases for all versions between 1.15 and 2.3. Patch releases for versions between 1.15 and 2.1 will also contain cherry-picks of f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Shuaike Dong, from Alipay Tian Qian Security Lab && Lab for Applied Security Research, CUHK.
- CVSS 3.1
- CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-20
- Also known as
- BIT-tensorflow-2020-15206, CVE-2020-15206, PYSEC-2020-129, PYSEC-2020-286, PYSEC-2020-321
- github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6g
- nvd.nist.gov/vuln/detail/CVE-2020-15206
- github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6
- github.com/tensorflow/tensorflow/commit/f760f88b4267d981e13f4b302c437ae800445968
- github.com/tensorflow/tensorflow/commit/fcfef195637c6e365577829c4d67681695956e7d
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-286.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-321.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-129.yaml
- github.com/tensorflow/tensorflow
- github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
More TensorFlow advisories
All TensorFlow| Date | Advisory | Severity | Fixed in |
|---|---|---|---|
| Sep 252020 | Out of bounds access in tensorflow-lite Critical8.1Sep 25, 2020 | Critical8.1 | 2.2.1+1 more |
| Sep 252020 | Out of bounds write in tensorflow-liteCritical8.1Sep 25, 2020 | Critical8.1 | 2.2.1+1 more |
| Sep 252020 | Denial of service in tensorflow-liteMedium4.0Sep 25, 2020 | Medium4.0 | 2.2.1+1 more |
| Sep 252020 | Segmentation fault in tensorflow-liteHigh6.5Sep 25, 2020 | High6.5 | 1.15.4+4 more |
| Sep 252020 | Out of bounds access in tensorflow-liteMedium4.8Sep 25, 2020 | Medium4.8 | 1.15.4+4 more |
| Sep 252020 | Null pointer dereference in tensorflow-liteHigh5.9Sep 25, 2020 | High5.9 | 1.15.4+4 more |