CVE-2020-15208 – tensorflow-gpu

Package

Manager: pip
Name: tensorflow-gpu
Vulnerable Version: >=0 <1.15.4 || >=2.0.0 <2.0.3 || >=2.1.0 <2.1.2 || =2.2.0 || >=2.2.0 <2.2.1 || =2.3.0 || >=2.3.0 <2.3.1

Severity

Level: High

CVSS v3.1: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N

CVSS v4.0: CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N

EPSS: 0.0033 pctl0.55359

Details

Data corruption in tensorflow-lite ### Impact When determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/types.h#L437-L442 Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. ### Patches We have patched the issue in 8ee24e7949a20 and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

Metadata

Created: 2020-09-25T18:28:44Z
Modified: 2024-10-30T21:17:24Z
Source: https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2020/09/GHSA-mxjj-953w-2c2v/GHSA-mxjj-953w-2c2v.json
CWE IDs: ["CWE-125", "CWE-787"]
Alternative ID: GHSA-mxjj-953w-2c2v
Finding: F111
Auto approve: 1