Out-of-bounds Write
CVE-2021-29536
Summary
TensorFlow is an end-to-end open source platform for machine learning. On versions before 2.1.4, 2.2.0 through 2.2.2, 2.3.0 through 2.3.2 and 2.4.0 through 2.4.1, an attacker can cause a heap buffer overflow in `QuantizedReshape` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a324ac84e573fba362a5e53d4e74d5de6729933e/tensorflow/core/kernels/quantized_reshape_op.cc#L38-L55) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow.
- LOW
- LOCAL
- HIGH
- UNCHANGED
- NONE
- LOW
- HIGH
- HIGH
CWE-787 - Out-of-Bounds Write
Out-of-bounds write vulnerability is a memory access bug that allows software to write data past the end or before the beginning of the intended buffer. This may result in the corruption of data, a crash, or arbitrary code execution.
References
Advisory Timeline
- Published