Improper resource allocation In tensorflow
Description
Memory leak in Tensorflow
Impact
If a graph node is invalid, TensorFlow can leak memory in the implementation of ImmutableExecutorState::Initialize:
Status s = params_.create_kernel(n->properties(), &item->kernel); if (!s.ok()) { item->kernel = nullptr; s = AttachDef(s, *n); return s; }
Here, we set item->kernel to nullptr but it is a simple OpKernel* pointer so the memory that was previously allocated to it would leak.
Patches
We have patched the issue in GitHub commit c79ccba517dbb1a0ccb9b01ee3bd2a63748b60dd. 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
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Mitigation
Update Impact
Minimal update. May introduce new vulnerabilities or breaking changes.
Ecosystem | Component | Affected version | Patched versions |
|---|---|---|---|
pypi | 2.5.3, 2.6.3, 2.7.1 | ||
pypi | 2.5.3, 2.6.3, 2.7.1 | ||
pypi | 2.5.3, 2.6.3, 2.7.1 |
Aliases
References