Crash when type cannot be specialized in Tensorflow

Summary

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the `DCHECK` function however, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.

Timeline

1. Feb 4, 2022, 10:32 PM UTCCVE published
2. Apr 22, 2025, 3:50 PM UTCCISA SSVC assessment

   Exploitation: poc · Automatable: no · Technical impact: partial

3. Apr 22, 2025, 6:24 PM UTCRecord last updated

Affected versions

• tensorflow tensorflow

  From 2.7.0 · fixed in 2.7.1; From 2.6.0 · fixed in 2.6.3; fixed in 2.5.3

• tensorflowPyPI

  fixed in 2.5.3; From 2.6.0 · fixed in 2.6.3; From 2.7.0 · fixed in 2.7.1

• tensorflowPyPI

  fixed in 2.5.3

• tensorflowPyPI

  From 2.6.0 · fixed in 2.6.3

• tensorflowPyPI

  From 2.7.0 · fixed in 2.7.1

• tensorflow-cpuPyPI

  fixed in 2.5.3

• tensorflow-cpuPyPI

  From 2.6.0 · fixed in 2.6.3

• tensorflow-cpuPyPI

  From 2.7.0 · fixed in 2.7.1

• tensorflow-gpuPyPI

  fixed in 2.5.3

• tensorflow-gpuPyPI

  From 2.6.0 · fixed in 2.6.3

• tensorflow-gpuPyPI

  From 2.7.0 · fixed in 2.7.1

• tensorflow-gpuPyPI

  fixed in 2.5.3; From 2.6.0 · fixed in 2.6.3

• tensorflow-cpuPyPI

  fixed in 2.5.3; From 2.6.0 · fixed in 2.6.3

References 3