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Vulnerability Intelligence
Miggo AI
Miggo AIMiggo AI| Package Name | Ecosystem | Vulnerable Versions | First Patched Version |
|---|---|---|---|
| tensorflow | pip | < 2.7.2 | 2.7.2 |
| tensorflow | pip | >= 2.8.0, < 2.8.1 | 2.8.1 |
| tensorflow | pip | >= 2.9.0, < 2.9.1 | 2.9.1 |
| tensorflow-cpu | pip | < 2.7.2 | 2.7.2 |
| tensorflow-cpu | pip | >= 2.8.0, < 2.8.1 | 2.8.1 |
| tensorflow-cpu | pip | >= 2.9.0, < 2.9.1 | 2.9.1 |
| tensorflow-gpu | pip | < 2.7.2 | 2.7.2 |
| tensorflow-gpu | pip | >= 2.8.0, < 2.8.1 | 2.8.1 |
| tensorflow-gpu | pip | >= 2.9.0, < 2.9.1 | 2.9.1 |
PythonPythonMiggo AIRoot Cause AnalysisThe vulnerability stems from missing validation in FractionalAvgPoolGrad's gradient computation. The commit diff shows added validation checks for:
These were absent in the original implementation, making the Compute function in fractional_avg_pool_op.cc the vulnerable entry point. The Python PoC demonstrates triggering via invalid orig_input_tensor_shape, which would pass through the unpatched validation that only checked tensor rank and element count, not individual dimension validity or overflow scenarios.
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