CVE-2021-41227: Arbitrary memory read in `ImmutableConst`
First published: Fri Nov 05 2021(Updated: )
### Impact The `ImmutableConst` operation in TensorFlow can be tricked into reading arbitrary memory contents: ```python import tensorflow as tf with open('/tmp/test','wb') as f: f.write(b'\xe2'*128) data = tf.raw_ops.ImmutableConst(dtype=tf.string,shape=3,memory_region_name='/tmp/test') print(data) ``` This is because the `tstring` TensorFlow string class has a special case for memory mapped strings but the operation itself does not offer any support for this datatype. ### Patches We have patched the issue in GitHub commit [3712a2d3455e6ccb924daa5724a3652a86f6b585](https://github.com/tensorflow/tensorflow/commit/3712a2d3455e6ccb924daa5724a3652a86f6b585) and GitHub commit [1cb6bb6c2a6019417c9adaf9e6843ba75ee2580b](https://github.com/tensorflow/tensorflow/commit/1cb6bb6c2a6019417c9adaf9e6843ba75ee2580b). The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. ### 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 | <2.4.4 | 2.4.4 |
| pip/tensorflow-gpu | >=2.5.0<2.5.2 | 2.5.2 |
| pip/tensorflow-gpu | >=2.6.0<2.6.1 | 2.6.1 |
| pip/tensorflow-cpu | <2.4.4 | 2.4.4 |
| pip/tensorflow-cpu | >=2.5.0<2.5.2 | 2.5.2 |
| pip/tensorflow-cpu | >=2.6.0<2.6.1 | 2.6.1 |
| pip/tensorflow | <2.4.4 | 2.4.4 |
| pip/tensorflow | >=2.5.0<2.5.2 | 2.5.2 |
| pip/tensorflow | >=2.6.0<2.6.1 | 2.6.1 |
| TensorFlow Keras | >=2.4.0<2.4.4 | |
| TensorFlow Keras | >=2.6.0<2.6.1 | |
| TensorFlow Keras | =2.7.0-rc0 | |
| TensorFlow Keras | =2.7.0-rc1 |
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Reference Links
- https://github.com/tensorflow/tensorflow/commit/1cb6bb6c2a6019417c9adaf9e6843ba75ee2580b
- https://github.com/tensorflow/tensorflow/commit/3712a2d3455e6ccb924daa5724a3652a86f6b585
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j8c8-67vp-6mx7
- https://nvd.nist.gov/vuln/detail/CVE-2021-41227
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-636.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-834.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-419.yaml
- https://github.com/advisories/GHSA-j8c8-67vp-6mx7 (Advisory)
Frequently Asked Questions
What is the severity of CVE-2021-41227?
CVE-2021-41227 has been classified as a high severity vulnerability due to its ability to potentially read arbitrary memory contents.
How do I fix CVE-2021-41227?
You can mitigate CVE-2021-41227 by upgrading TensorFlow to version 2.4.4 or later, specifically to versions 2.5.2 or 2.6.1.
What versions of TensorFlow are affected by CVE-2021-41227?
CVE-2021-41227 affects TensorFlow versions from 2.4.0 up to but not including 2.4.4, as well as 2.6.0 to 2.6.1.
How does CVE-2021-41227 impact TensorFlow users?
CVE-2021-41227 may allow an attacker to access sensitive information from memory, posing a risk to data security.
Is CVE-2021-41227 being actively exploited in the wild?
As of now, there are no confirmed reports of active exploitation of CVE-2021-41227.
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