Buffer overflow in the array_from_pyobj function of fortranobject.c in NumPy < 1.19, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally)
References
| Link | Resource |
|---|---|
| https://github.com/numpy/numpy/issues/19000 | Exploit Issue Tracking Patch Third Party Advisory |
| https://www.oracle.com/security-alerts/cpujul2022.html | Third Party Advisory |
| https://github.com/numpy/numpy/issues/19000 | Exploit Issue Tracking Patch Third Party Advisory |
| https://www.oracle.com/security-alerts/cpujul2022.html | Third Party Advisory |
Configurations
History
21 Nov 2024, 06:26
| Type | Values Removed | Values Added |
|---|---|---|
| References | () https://github.com/numpy/numpy/issues/19000 - Exploit, Issue Tracking, Patch, Third Party Advisory | |
| References | () https://www.oracle.com/security-alerts/cpujul2022.html - Third Party Advisory |
07 Nov 2023, 03:38
| Type | Values Removed | Values Added |
|---|---|---|
| Summary | Buffer overflow in the array_from_pyobj function of fortranobject.c in NumPy < 1.19, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally) |
Information
Published : 2021-12-17 20:15
Updated : 2024-11-21 06:26
NVD link : CVE-2021-41496
Mitre link : CVE-2021-41496
CVE.ORG link : CVE-2021-41496
JSON object : View
Products Affected
numpy
- numpy
CWE
CWE-120
Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')