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Numpy missing input validation

High severity GitHub Reviewed Published May 13, 2022 to the GitHub Advisory Database • Updated Jan 27, 2023

Package

pip numpy (pip)

Affected versions

< 1.13.3

Patched versions

1.13.3

Description

The numpy.pad function in Numpy 1.13.1 and older versions is missing input validation. An empty list or ndarray will stick into an infinite loop, which can allow attackers to cause a DoS attack.

References

Published by the National Vulnerability Database Aug 15, 2017
Published to the GitHub Advisory Database May 13, 2022
Reviewed Jun 17, 2022
Last updated Jan 27, 2023

Severity

High

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
Network
Attack complexity
Low
Privileges required
None
User interaction
None
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:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

EPSS score

0.170%
(55th percentile)

Weaknesses

CVE ID

CVE-2017-12852

GHSA ID

GHSA-frgw-fgh6-9g52

Source code

Credits

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