CVE-2021-29535 | Date: (C)2021-05-17 (M)2023-12-22 |
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedMul` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/87cf4d3ea9949051e50ca3f071fc909538a51cd0/tensorflow/core/kernels/quantized_mul_op.cc#L287-L290) assumes that the 4 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat()` 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.
CVSS Score and Metrics +CVSS Score and Metrics -CVSS V3 Severity: | CVSS V2 Severity: |
CVSS Score : 7.8 | CVSS Score : 4.6 |
Exploit Score: 1.8 | Exploit Score: 3.9 |
Impact Score: 5.9 | Impact Score: 6.4 |
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CVSS V3 Metrics: | CVSS V2 Metrics: |
Attack Vector: LOCAL | Access Vector: LOCAL |
Attack Complexity: LOW | Access Complexity: LOW |
Privileges Required: LOW | Authentication: NONE |
User Interaction: NONE | Confidentiality: PARTIAL |
Scope: UNCHANGED | Integrity: PARTIAL |
Confidentiality: HIGH | Availability: PARTIAL |
Integrity: HIGH | |
Availability: HIGH | |
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