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CVE-2021-29535
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Date: May 14, 2021
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<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.
Language: Python
Severity Score
Related Resources (8)
Severity Score
Top Fix
CVSS v3.1
| Base Score: |
|
|---|---|
| Attack Vector (AV): | LOCAL |
| Attack Complexity (AC): | HIGH |
| Privileges Required (PR): | LOW |
| User Interaction (UI): | NONE |
| Scope (S): | UNCHANGED |
| Confidentiality (C): | NONE |
| Integrity (I): | NONE |
| Availability (A): | LOW |
CVSS v2
| Base Score: |
|
|---|---|
| Access Vector (AV): | LOCAL |
| Access Complexity (AC): | LOW |
| Authentication (AU): | NONE |
| Confidentiality (C): | PARTIAL |
| Integrity (I): | PARTIAL |
| Availability (A): | PARTIAL |
| Additional information: |