CVE-2021-29535

LOW

TensorFlow < 2.1.4 - Heap Buffer Overflow in QuantizedMul via Invalid Quantization Thresholds

Title source: llm
STIX 2.1

Description

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.

References (2)

Core 2
Core References
Exploit, Patch, Third Party Advisory x_refsource_confirm
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m3f9-w3p3-p669

Scores

CVSS v3 2.5
EPSS 0.0021
EPSS Percentile 11.3%
Attack Vector LOCAL
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

Details

CWE
CWE-131 CWE-787
Status published
Products (4)
google/tensorflow < 2.1.4
pypi/tensorflow 0 - 2.1.4PyPI
pypi/tensorflow-cpu 0 - 2.1.4PyPI
pypi/tensorflow-gpu 0 - 2.1.4PyPI
Published May 14, 2021
Tracked Since Feb 18, 2026