Division by zero in TFLite

Overview

Impact

An attacker can craft a TFLite model that would trigger a division by zero in BiasAndClamp implementation:

inline void BiasAndClamp(float clamp_min, float clamp_max, int bias_size,
                         const float* bias_data, int array_size,
                         float* array_data) {
  // ...
  TFLITE_DCHECK_EQ((array_size % bias_size), 0);
  // ...
} 

There is no check that the bias_size is non zero.

Patches

We have patched the issue in GitHub commit 8c6f391a2282684a25cbfec7687bd5d35261a209.

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.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Wang Xuan of Qihoo 360 AIVul Team.

Affected packages

• tensorflow < 2.5.3
• tensorflow >= 2.6.0, < 2.6.3
• tensorflow >= 2.7.0, < 2.7.1
• tensorflow-cpu < 2.5.3
• tensorflow-cpu >= 2.6.0, < 2.6.3
• tensorflow-cpu >= 2.7.0, < 2.7.1
• tensorflow-gpu < 2.5.3
• tensorflow-gpu >= 2.6.0, < 2.6.3
• tensorflow-gpu >= 2.7.0, < 2.7.1

Remediation

Upgrade to a patched release:

• tensorflow 2.5.3
• tensorflow 2.6.3
• tensorflow 2.7.1
• tensorflow-cpu 2.5.3
• tensorflow-cpu 2.6.3
• tensorflow-cpu 2.7.1
• tensorflow-gpu 2.5.3
• tensorflow-gpu 2.6.3
• tensorflow-gpu 2.7.1