CVE-2021-41195: Crash in `tf.math.segment_*` operations
First published: Fri Nov 05 2021(Updated: )
### Impact The implementation of `tf.math.segment_*` operations results in a `CHECK`-fail related abort (and denial of service) if a segment id in `segment_ids` is large. ```python import tensorflow as tf tf.math.segment_max(data=np.ones((1,10,1)), segment_ids=[1676240524292489355]) tf.math.segment_min(data=np.ones((1,10,1)), segment_ids=[1676240524292489355]) tf.math.segment_mean(data=np.ones((1,10,1)), segment_ids=[1676240524292489355]) tf.math.segment_sum(data=np.ones((1,10,1)), segment_ids=[1676240524292489355]) tf.math.segment_prod(data=np.ones((1,10,1)), segment_ids=[1676240524292489355]) ``` This is similar to [CVE-2021-29584](https://github.com/tensorflow/tensorflow/blob/3a74f0307236fe206b046689c4d76f57c9b74eee/tensorflow/security/advisory/tfsa-2021-071.md) (and similar other reported vulnerabilities in TensorFlow, localized to specific APIs): the [implementation](https://github.com/tensorflow/tensorflow/blob/dae66e518c88de9c11718cd0f8f40a0b666a90a0/tensorflow/core/kernels/segment_reduction_ops_impl.h) (both on CPU and GPU) computes the output shape using [`AddDim`](https://github.com/tensorflow/tensorflow/blob/0b6b491d21d6a4eb5fbab1cca565bc1e94ca9543/tensorflow/core/framework/tensor_shape.cc#L395-L408). However, if the number of elements in the tensor overflows an `int64_t` value, `AddDim` results in a `CHECK` failure which provokes a `std::abort`. Instead, code should use [`AddDimWithStatus`](https://github.com/tensorflow/tensorflow/blob/0b6b491d21d6a4eb5fbab1cca565bc1e94ca9543/tensorflow/core/framework/tensor_shape.cc#L410-L440). ### Patches We have patched the issue in GitHub commit [e9c81c1e1a9cd8dd31f4e83676cab61b60658429](https://github.com/tensorflow/tensorflow/commit/e9c81c1e1a9cd8dd31f4e83676cab61b60658429) (merging [#51733](https://github.com/tensorflow/tensorflow/pull/51733)). 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 externally via a [GitHub issue](https://github.com/tensorflow/tensorflow/issues/46888).
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| Google TensorFlow | <2.4.4 | |
| Google TensorFlow | >=2.5.0<2.5.2 | |
| Google TensorFlow | >=2.6.0<2.6.1 | |
| 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 |
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Reference Links
- https://github.com/tensorflow/tensorflow/commit/e9c81c1e1a9cd8dd31f4e83676cab61b60658429
- https://github.com/tensorflow/tensorflow/issues/46888
- https://github.com/tensorflow/tensorflow/pull/51733
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cq76-mxrc-vchh
- https://nvd.nist.gov/vuln/detail/CVE-2021-41195
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-844.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-846.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-842.yaml
- https://github.com/advisories/GHSA-cq76-mxrc-vchh (Advisory)
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