CVE-2020-15203: Denial of Service in Tensorflow
First published: Fri Sep 25 2020(Updated: )
### Impact By controlling the `fill` argument of [`tf.strings.as_string`](https://www.tensorflow.org/api_docs/python/tf/strings/as_string), a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a `printf` call is constructed: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/as_string_op.cc#L68-L74 This can result in unexpected output: ```python In [1]: tf.strings.as_string(input=[1234], width=6, fill='-') Out[1]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['1234 '], dtype=object)> In [2]: tf.strings.as_string(input=[1234], width=6, fill='+') Out[2]: <tf.Tensor: shape=(1,), dtype=string, numpy=array([' +1234'], dtype=object)> In [3]: tf.strings.as_string(input=[1234], width=6, fill="h") Out[3]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['%6d'], dtype=object)> In [4]: tf.strings.as_string(input=[1234], width=6, fill="d") Out[4]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['12346d'], dtype=object)> In [5]: tf.strings.as_string(input=[1234], width=6, fill="o") Out[5]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['23226d'], dtype=object)> In [6]: tf.strings.as_string(input=[1234], width=6, fill="x") Out[6]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['4d26d'], dtype=object)> In [7]: tf.strings.as_string(input=[1234], width=6, fill="g") Out[7]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['8.67458e-3116d'], dtype=object)> In [8]: tf.strings.as_string(input=[1234], width=6, fill="a") Out[8]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['0x0.00ff7eebb4d4p-10226d'], dtype=object)> In [9]: tf.strings.as_string(input=[1234], width=6, fill="c") Out[9]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['\xd26d'], dtype=object)> In [10]: tf.strings.as_string(input=[1234], width=6, fill="p") Out[10]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['0x4d26d'], dtype=object)> In [11]: tf.strings.as_string(input=[1234], width=6, fill='m') Out[11]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['Success6d'], dtype=object)> ``` However, passing in `n` or `s` results in segmentation fault. ### Patches We have patched the issue in 33be22c65d86256e6826666662e40dbdfe70ee83 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. ### 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 members of the Aivul Team from Qihoo 360.
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| pip/tensorflow-gpu | =2.3.0 | 2.3.1 |
| pip/tensorflow-gpu | =2.2.0 | 2.2.1 |
| pip/tensorflow-gpu | >=2.1.0<2.1.2 | 2.1.2 |
| pip/tensorflow-gpu | >=2.0.0<2.0.3 | 2.0.3 |
| pip/tensorflow-gpu | <1.15.4 | 1.15.4 |
| pip/tensorflow-cpu | =2.3.0 | 2.3.1 |
| pip/tensorflow-cpu | =2.2.0 | 2.2.1 |
| pip/tensorflow-cpu | >=2.1.0<2.1.2 | 2.1.2 |
| pip/tensorflow-cpu | >=2.0.0<2.0.3 | 2.0.3 |
| pip/tensorflow-cpu | <1.15.4 | 1.15.4 |
| pip/tensorflow | =2.3.0 | 2.3.1 |
| pip/tensorflow | =2.2.0 | 2.2.1 |
| pip/tensorflow | >=2.1.0<2.1.2 | 2.1.2 |
| pip/tensorflow | >=2.0.0<2.0.3 | 2.0.3 |
| pip/tensorflow | <1.15.4 | 1.15.4 |
| Google TensorFlow | <1.15.4 | |
| Google TensorFlow | >=2.0.0<2.0.3 | |
| Google TensorFlow | >=2.1.0<2.1.2 | |
| Google TensorFlow | >=2.2.0<2.2.1 | |
| Google TensorFlow | >=2.3.0<2.3.1 | |
| openSUSE | =15.2 |
Never miss a vulnerability like this again
Sign up to SecAlerts for real-time vulnerability data matched to your software, aggregated from hundreds of sources.
Reference Links
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
- https://github.com/tensorflow/tensorflow/commit/33be22c65d86256e6826666662e40dbdfe70ee83
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xmq7-7fxm-rr79
- https://nvd.nist.gov/vuln/detail/CVE-2020-15203
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-283.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-318.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-126.yaml
- https://github.com/advisories/GHSA-xmq7-7fxm-rr79 (Advisory)
- agent/type
- collector/mitre-cve
- source/MITRE
- agent/title
- agent/remedy
- agent/severity
- agent/weakness
- collector/github-advisory-latest
- source/GitHub
- alias/GHSA-xmq7-7fxm-rr79
- alias/CVE-2020-15203
- agent/software-canonical-lookup
- agent/references
- agent/last-modified-date
- agent/softwarecombine
- agent/description
- agent/event
- agent/first-publish-date
- agent/author
- collector/github-advisory
- agent/trending
- agent/source
- agent/tags
- collector/nvd-cve
- source/NVD
- agent/software-canonical-lookup-request
- collector/nvd-index
- package-manager/pip
- vendor/google
- canonical/google tensorflow
- version/google tensorflow/2.0.0
- version/google tensorflow/2.1.0
- version/google tensorflow/2.2.0
- version/google tensorflow/2.3.0
- vendor/opensuse
- canonical/opensuse
- version/opensuse/15.2