Vulnerability CVE-2021-29535


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 `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.

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
Affected software
Google -> Tensorflow 

 References:
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m3f9-w3p3-p669
https://github.com/tensorflow/tensorflow/commit/efea03b38fb8d3b81762237dc85e579cc5fc6e87

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