CVSS: 6.5EPSS: 0%CPEs: 3EXPL: 1CVE-2022-23567 – Integer overflows in Tensorflow
https://notcve.org/view.php?id=CVE-2022-23567
Tensorflow is an Open Source Machine Learning Framework. The implementations of `Sparse*Cwise*` ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. • https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md https://github.com/tensorflow/tensorflow/commit/1b54cadd19391b60b6fcccd8d076426f7221d5e8 https://github.com/tensorflow/tensorflow/commit/e952a89b7026b98fe8cbe626514a93ed68b7c510 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrx2-r989-2c43 • CWE-190: Integer Overflow or Wraparound •
CVSS: 6.5EPSS: 0%CPEs: 3EXPL: 1CVE-2022-23568 – Integer overflows in Tensorflow
https://notcve.org/view.php?id=CVE-2022-23568
Tensorflow is an Open Source Machine Learning Framework. The implementation of `AddManySparseToTensorsMap` is vulnerable to an integer overflow which results in a `CHECK`-fail when building new `TensorShape` objects (so, an assert failure based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. 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. • https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_tensors_map_ops.cc https://github.com/tensorflow/tensorflow/commit/a68f68061e263a88321c104a6c911fe5598050a8 https://github.com/tensorflow/tensorflow/commit/b51b82fe65ebace4475e3c54eb089c18a4403f1c https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6445-fm66-fvq2 • CWE-190: Integer Overflow or Wraparound •
CVSS: 6.5EPSS: 0%CPEs: 3EXPL: 2CVE-2022-21731 – Type confusion leading to segfault in Tensorflow
https://notcve.org/view.php?id=CVE-2022-21731
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. • https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/common_shape_fns.cc#L1961-L2059 https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.cc#L345-L358 https://github.com/tensorflow/tensorflow/commit/08d7b00c0a5a20926363849f611729f53f3ec022 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m4hf-j54p-p353 • CWE-843: Access of Resource Using Incompatible Type ('Type Confusion') •
CVSS: 6.5EPSS: 0%CPEs: 3EXPL: 1CVE-2022-21733 – Memory exhaustion in Tensorflow
https://notcve.org/view.php?id=CVE-2022-21733
Tensorflow is an Open Source Machine Learning Framework. The implementation of `StringNGrams` can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on `pad_witdh` and that result in computing a negative value for `ngram_width` which is later used to allocate parts of the output. 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. • https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/string_ngrams_op.cc#L29-L161 https://github.com/tensorflow/tensorflow/commit/f68fdab93fb7f4ddb4eb438c8fe052753c9413e8 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-98j8-c9q4-r38g • CWE-190: Integer Overflow or Wraparound •
CVSS: 6.5EPSS: 0%CPEs: 3EXPL: 1CVE-2022-21732 – Memory exhaustion in Tensorflow
https://notcve.org/view.php?id=CVE-2022-21732
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. • https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc#L79-L135 https://github.com/tensorflow/tensorflow/commit/e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c582-c96p-r5cq • CWE-770: Allocation of Resources Without Limits or Throttling •