CVE-2022-35940Medium· 5.9▾ SunlitTensorFlow vulnerable to Int overflow in `RaggedRangeOp`
▾ Sunlit zone — Low / medium · no exploitation signal
impact 32.5 · likelihood 0.1 · exploitation 0
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Exploit-prediction probability, daily snapshots since Jul 8.
Disclosure to exploitation, from the record and what we observed since indexing it.
Disclosed via OSV
Last analysed / modified upstream
0.5%
0.5% → 0.7%
The RaggedRangOp function takes an argument limits that is eventually used to construct a TensorShape as an int64. If limits is a very large float, it can overflow when converted to an int64. This triggers an InvalidArgument but also throws an abort signal that crashes the program.
import tensorflow as tf
tf.raw_ops.RaggedRange(starts=[1.1,0.1],limits=[10.0,1e20],deltas=[1,1])
We have patched the issue in GitHub commit 37cefa91bee4eace55715eeef43720b958a01192.
The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.
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This vulnerability has been reported by Jingyi Shi.
tensorflow < 2.7.2tensorflow >= 2.8.0, < 2.8.1tensorflow >= 2.9.0, < 2.9.1tensorflow-cpu < 2.7.2tensorflow-cpu >= 2.8.0, < 2.8.1tensorflow-cpu >= 2.9.0, < 2.9.1tensorflow-gpu < 2.7.2tensorflow-gpu >= 2.8.0, < 2.8.1tensorflow-gpu >= 2.9.0, < 2.9.1Upgrade to a patched release:
tensorflow 2.7.2tensorflow 2.8.1tensorflow 2.9.1tensorflow-cpu 2.7.2tensorflow-cpu 2.8.1tensorflow-cpu 2.9.1tensorflow-gpu 2.7.2tensorflow-gpu 2.8.1tensorflow-gpu 2.9.1Connected by shared product, vendor, weakness, or advisory.
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CVE-2022-35987Medium· 5.9TensorFlow vulnerable to `CHECK` fail in `DenseBincount`
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