Segfault in `tf.quantization.quantize_and_dequantize`
Impact
An attacker can pass an invalid axis value to tf.quantization.quantize_and_dequantize:
```python
tf.quantization.quantize_and_dequantize(
input=[2.5, 2.5], input_min=[0,0], input_max=[1,1], axis=10)
`
This results in accessing [a dimension outside the rank of the input tensor](https://github.com/tensorflow/tensorflow/blob/0225022b725993bfc19b87a02a2faaad9a53bc17/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L74) in the C++ kernel implementation:
`
const int depth = (axis_ == -1) ? 1 : input.dim_size(axis_);
`
However, [dim_size only does a DCHECK](https://github.com/tensorflow/tensorflow/blob/0225022b725993bfc19b87a02a2faaad9a53bc17/tensorflow/core/framework/tensor_shape.cc#L292-L307) to validate the argument and then uses it to access the corresponding element of an array:
`
int64 TensorShapeBase<Shape>::dim_size(int d) const {
DCHECK_GE(d, 0);
DCHECK_LT(d, dims());
DoStuffWith(dims_[d]);
}
`
Since in normal builds, DCHECK-like macros are no-ops, this results in segfault and access out of bounds of the array.
Patches
We have patched the issue in eccb7ec454e6617738554a255d77f08e60ee0808 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
For more information
Please consult [our security...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.4.0 | 2.4.0 |
Details and references
### Impact An attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`: ```python tf.quantization.quantize_and_dequantize( input=[2.5, 2.5], input_min=[0,0], input_max=[1,1], axis=10) ``` This results in accessing [a dimension outside the rank of the input tensor](https://github.com/tensorflow/tensorflow/blob/0225022b725993bfc19b87a02a2faaad9a53bc17/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L74) in the C++ kernel implementation: ``` const int depth = (axis_ == -1) ? 1 : input.dim_size(axis_); ``` However, [`dim_size` only does a `DCHECK`](https://github.com/tensorflow/tensorflow/blob/0225022b725993bfc19b87a02a2faaad9a53bc17/tensorflow/core/framework/tensor_shape.cc#L292-L307) to validate the argument and then uses it to access the corresponding element of an array: ``` int64 TensorShapeBase<Shape>::dim_size(int d) const { DCHECK_GE(d, 0); DCHECK_LT(d, dims()); DoStuffWith(dims_[d]); } ``` Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. ### Patches We have patched the issue in eccb7ec454e6617738554a255d77f08e60ee0808 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported in #42105
- CVSS 3.1
- CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-125
- Also known as
- BIT-tensorflow-2020-15265, CVE-2020-15265, PYSEC-2020-138, PYSEC-2020-295, PYSEC-2020-330
- github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c
- nvd.nist.gov/vuln/detail/CVE-2020-15265
- github.com/tensorflow/tensorflow/issues/42105
- github.com/tensorflow/tensorflow/commit/eccb7ec454e6617738554a255d77f08e60ee0808
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-295.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-330.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-138.yaml
- github.com/tensorflow/tensorflow