Tensorflow is an Open Source Machine Learning Framework. The implementation of `ThreadPoolHandle` can be used to trigger a denial of service attack by allocating too much memory. This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
References
Link | Resource |
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https://github.com/tensorflow/tensorflow/commit/e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e | Patch Third Party Advisory |
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c582-c96p-r5cq | Patch Third Party Advisory |
https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc#L79-L135 | Exploit Third Party Advisory |
Configurations
Configuration 1 (hide)
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Information
Published : 2022-02-03 04:15
Updated : 2022-02-08 19:08
NVD link : CVE-2022-21732
Mitre link : CVE-2022-21732
JSON object : View
CWE
CWE-770
Allocation of Resources Without Limits or Throttling
Products Affected
- tensorflow