The TensorFlow Authors

107 exploits Active since May 2021
CVE-2022-29205 WRITEUP MEDIUM WRITEUP
TensorFlow <2.9.0-2.6.4 - Use After Free
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, there is a potential for segfault / denial of service in TensorFlow by calling `tf.compat.v1.*` ops which don't yet have support for quantized types, which was added after migration to TensorFlow 2.x. In these scenarios, since the kernel is missing, a `nullptr` value is passed to `ParseDimensionValue` for the `py_value` argument. Then, this is dereferenced, resulting in segfault. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
CVE-2022-29211 WRITEUP MEDIUM WRITEUP
TensorFlow <2.9.0, <2.8.1, <2.7.2, <2.6.4 - Memory Corruption
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.histogram_fixed_width` is vulnerable to a crash when the values array contain `Not a Number` (`NaN`) elements. The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index. If `values` contains `NaN` then the result of the division is still `NaN` and the cast to `int32` would result in a crash. This only occurs on the CPU implementation. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
CVSS 5.5
CVE-2022-41883 WRITEUP MEDIUM WRITEUP
TensorFlow 2.8.0-2.10.0 - Out-of-bounds Read in Dynamic Stitch Op
TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
CVSS 6.8
CVE-2022-41887 WRITEUP MEDIUM WRITEUP
TensorFlow 2.9.0-2.9.2 - Denial of Service via Integer Overflow in tf.keras.losses.poisson
TensorFlow is an open source platform for machine learning. `tf.keras.losses.poisson` receives a `y_pred` and `y_true` that are passed through `functor::mul` in `BinaryOp`. If the resulting dimensions overflow an `int32`, TensorFlow will crash due to a size mismatch during broadcast assignment. We have patched the issue in GitHub commit c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 and 2.9.3, as these are also affected and still in supported range. However, we will not cherrypick this commit into TensorFlow 2.8.x, as it depends on Eigen behavior that changed between 2.8 and 2.9.
CVSS 4.8
CVE-2022-41893 WRITEUP MEDIUM WRITEUP
TensorFlow < 2.8.4 - Denial of Service via tf.raw_ops.TensorListResize
TensorFlow is an open source platform for machine learning. If `tf.raw_ops.TensorListResize` is given a nonscalar value for input `size`, it results `CHECK` fail which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 888e34b49009a4e734c27ab0c43b0b5102682c56. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
CVSS 4.8
CVE-2022-41896 WRITEUP MEDIUM WRITEUP
TensorFlow < 2.8.4 - Denial of Service via ThreadUnsafeUnigramCandidateSampler Input Validation
TensorFlow is an open source platform for machine learning. If `ThreadUnsafeUnigramCandidateSampler` is given input `filterbank_channel_count` greater than the allowed max size, TensorFlow will crash. We have patched the issue in GitHub commit 39ec7eaf1428e90c37787e5b3fbd68ebd3c48860. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
CVSS 4.8
CVE-2022-41899 WRITEUP MEDIUM WRITEUP
TensorFlow < 2.8.4 - Reachable Assertion in SdcaOptimizer
TensorFlow is an open source platform for machine learning. Inputs `dense_features` or `example_state_data` not of rank 2 will trigger a `CHECK` fail in `SdcaOptimizer`. We have patched the issue in GitHub commit 80ff197d03db2a70c6a111f97dcdacad1b0babfa. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
CVSS 4.8