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Vulnerability CVE-2021-29536
Published: 2021-05-14
Description: |
TensorFlow is an end-to-end open source platform for machine learning. 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. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. |
Type:
CWE-787
CVSS2 => (AV:L/AC:L/Au:N/C:P/I:P/A:P)
CVSS Base Score |
Impact Subscore |
Exploitability Subscore |
4.6/10 |
6.4/10 |
3.9/10 |
Exploit range |
Attack complexity |
Authentication |
Local |
Low |
No required |
Confidentiality impact |
Integrity impact |
Availability impact |
Partial |
Partial |
Partial |
References: |
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2gfx-95x2-5v3x
https://github.com/tensorflow/tensorflow/commit/a324ac84e573fba362a5e53d4e74d5de6729933e
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