CVE-2021-29543: CHECK-fail in `CTCGreedyDecoder`
First published: Fri May 14 2021(Updated: )
### Impact An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.CTCGreedyDecoder`: ```python import tensorflow as tf inputs = tf.constant([], shape=[18, 2, 0], dtype=tf.float32) sequence_length = tf.constant([-100, 17], shape=[2], dtype=tf.int32) merge_repeated = False tf.raw_ops.CTCGreedyDecoder(inputs=inputs, sequence_length=sequence_length, merge_repeated=merge_repeated) ``` This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/1615440b17b364b875eb06f43d087381f1460a65/tensorflow/core/kernels/ctc_decoder_ops.cc#L37-L50) has a `CHECK_LT` inserted to validate some invariants. When this condition is false, the program aborts, instead of returning a valid error to the user. This abnormal termination can be weaponized in denial of service attacks. ### Patches We have patched the issue in GitHub commit [ea3b43e98c32c97b35d52b4c66f9107452ca8fb2](https://github.com/tensorflow/tensorflow/commit/ea3b43e98c32c97b35d52b4c66f9107452ca8fb2). The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Yakun Zhang and Ying Wang of Baidu X-Team.
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| Google TensorFlow | <2.1.4 | |
| Google TensorFlow | >=2.2.0<2.2.3 | |
| Google TensorFlow | >=2.3.0<2.3.3 | |
| Google TensorFlow | >=2.4.0<2.4.2 | |
| pip/tensorflow-gpu | >=2.4.0<2.4.2 | 2.4.2 |
| pip/tensorflow-gpu | >=2.3.0<2.3.3 | 2.3.3 |
| pip/tensorflow-gpu | >=2.2.0<2.2.3 | 2.2.3 |
| pip/tensorflow-gpu | <2.1.4 | 2.1.4 |
| pip/tensorflow-cpu | >=2.4.0<2.4.2 | 2.4.2 |
| pip/tensorflow-cpu | >=2.3.0<2.3.3 | 2.3.3 |
| pip/tensorflow-cpu | >=2.2.0<2.2.3 | 2.2.3 |
| pip/tensorflow-cpu | <2.1.4 | 2.1.4 |
| pip/tensorflow | >=2.4.0<2.4.2 | 2.4.2 |
| pip/tensorflow | >=2.3.0<2.3.3 | 2.3.3 |
| pip/tensorflow | >=2.2.0<2.2.3 | 2.2.3 |
| pip/tensorflow | <2.1.4 | 2.1.4 |
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Reference Links
- https://github.com/tensorflow/tensorflow/commit/ea3b43e98c32c97b35d52b4c66f9107452ca8fb2
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fphq-gw9m-ghrv
- https://nvd.nist.gov/vuln/detail/CVE-2021-29543
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-471.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-669.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-180.yaml
- https://github.com/advisories/GHSA-fphq-gw9m-ghrv (Advisory)
Frequently Asked Questions
What is the severity of CVE-2021-29543?
CVE-2021-29543 has a severity rating that indicates it can lead to denial of service.
How do I fix CVE-2021-29543?
To mitigate CVE-2021-29543, upgrade to TensorFlow versions 2.1.4, 2.2.3, 2.3.3, or 2.4.2.
What is the impact of CVE-2021-29543?
CVE-2021-29543 allows an attacker to trigger a denial of service through a CHECK-fail in tf.raw_ops.CTCGreedyDecoder.
Which versions of TensorFlow are affected by CVE-2021-29543?
CVE-2021-29543 affects TensorFlow versions prior to 2.1.4, between 2.2.0 and 2.2.3, between 2.3.0 and 2.3.3, and between 2.4.0 and 2.4.2.
Is CVE-2021-29543 related to a specific TensorFlow operation?
Yes, CVE-2021-29543 is specifically related to the tf.raw_ops.CTCGreedyDecoder operation in TensorFlow.
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