Heap OOB read in shape inference for `QuantizeV2`
Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
| Vendor | Product | Default status | Versions | ||||||
|---|---|---|---|---|---|---|---|---|---|
| tensorflow | tensorflow | affected |
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| Source | ID | Title |
|---|---|---|
EUVD |
EUVD-2021-0433 | TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `QuantizeV2` can trigger a read outside of bounds of heap allocated array. This occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer. The code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected. |
Github GHSA |
GHSA-cvgx-3v3q-m36c | Heap OOB in shape inference for `QuantizeV2` |
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This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.208% probability within 30 days)
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