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Improper Input Validation in OpenCV

Moderate severity GitHub Reviewed Published Oct 12, 2021 to the GitHub Advisory Database • Updated Jan 9, 2023

Package

pip opencv-contrib-python (pip)

Affected versions

<= 3.3.0.10

Patched versions

3.3.1.11
pip opencv-python (pip)
<= 3.3.0.10
3.3.1.11

Description

OpenCV 3.0.0 allows remote attackers to cause a denial of service (segfault) via vectors involving corrupt chunks. This issue was fixed in OpenCV version 3.3.1 (corresponding to OpenCV 3.3.1.11).

References

Reviewed Oct 8, 2021
Published to the GitHub Advisory Database Oct 12, 2021
Last updated Jan 9, 2023

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v3 base metrics

Attack vector
Local
Attack complexity
Low
Privileges required
None
User interaction
Required
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H

EPSS score

0.130%
(49th percentile)

Weaknesses

CVE ID

CVE-2016-1517

GHSA ID

GHSA-fffj-9qwg-qmh5

Source code

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