CVE-2021-29593Low· 2.5▾ SunlitDivision by zero in TFLite's implementation of `BatchToSpaceNd`
▾ Sunlit zone — Low / medium · no exploitation signal
impact 13.8 · likelihood 0 · 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
0.2%
The implementation of the BatchToSpaceNd TFLite operator is vulnerable to a division by zero error:
TF_LITE_ENSURE_EQ(context, output_batch_size % block_shape[dim], 0);
output_batch_size = output_batch_size / block_shape[dim];
An attacker can craft a model such that one dimension of the block input is 0. Hence, the corresponding value in block_shape is 0.
We have patched the issue in GitHub commit 2c74674348a4708ced58ad6eb1b23354df8ee044.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
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This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
tensorflow < 2.1.4tensorflow >= 2.2.0, < 2.2.3tensorflow >= 2.3.0, < 2.3.3tensorflow >= 2.4.0, < 2.4.2tensorflow-cpu < 2.1.4tensorflow-cpu >= 2.2.0, < 2.2.3tensorflow-cpu >= 2.3.0, < 2.3.3tensorflow-cpu >= 2.4.0, < 2.4.2tensorflow-gpu < 2.1.4tensorflow-gpu >= 2.2.0, < 2.2.3tensorflow-gpu >= 2.3.0, < 2.3.3tensorflow-gpu >= 2.4.0, < 2.4.2Upgrade to a patched release:
tensorflow 2.1.4tensorflow 2.2.3tensorflow 2.3.3tensorflow 2.4.2tensorflow-cpu 2.1.4tensorflow-cpu 2.2.3tensorflow-cpu 2.3.3tensorflow-cpu 2.4.2tensorflow-gpu 2.1.4tensorflow-gpu 2.2.3tensorflow-gpu 2.3.3tensorflow-gpu 2.4.2Connected by shared product, vendor, weakness, or advisory.
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