Vulnerability Details : CVE-2021-41203

TensorFlow is an open source platform for machine learning. In affected versions an attacker can trigger undefined behavior, integer overflows, segfaults and `CHECK`-fail crashes if they can change saved checkpoints from outside of TensorFlow. This is because the checkpoints loading infrastructure is missing validation for invalid file formats. The fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
Vulnerability category: Overflow
Published 2021-11-05 21:15:09
Updated 2022-10-20 21:36:58
Source GitHub, Inc.
View at NVD,   CVE.org

Exploit prediction scoring system (EPSS) score for CVE-2021-41203

Probability of exploitation activity in the next 30 days: 0.05%

Percentile, the proportion of vulnerabilities that are scored at or less: ~ 12 % EPSS Score History EPSS FAQ

CVSS scores for CVE-2021-41203

Base Score Base Severity CVSS Vector Exploitability Score Impact Score Source
4.6
 MEDIUM AV:L/AC:L/Au:N/C:P/I:P/A:P
3.9
6.4
 nvd@nist.gov
7.8
 HIGH CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
1.8
5.9
 nvd@nist.gov
7.8
 HIGH CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
1.8
5.9
 security-advisories@github.com

CWE ids for CVE-2021-41203

  • The product performs a calculation that can produce an integer overflow or wraparound, when the logic assumes that the resulting value will always be larger than the original value. This can introduce other weaknesses when the calculation is used for resource management or execution control.
    Assigned by: nvd@nist.gov (Primary)
  • The product does not sufficiently verify the origin or authenticity of data, in a way that causes it to accept invalid data.
    Assigned by: security-advisories@github.com (Secondary)

References for CVE-2021-41203

Products affected by CVE-2021-41203

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