PatchTheCVECVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c in NumPy < 1.19, which allows attackers to
CVE-2021-41496 is a medium-severity flaw (CVSS 5.5) affecting numpy. Below: why it ranks where it does, which versions are affected, what to do, and the exact commands.
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)
Why this priority
- Public exploit reference
A fixed release or distro patch exists.
Risk facts
| CVSS score | 5.5 (Medium) |
| Attack vector | Local |
| Attack complexity | Low |
| Privileges needed | Low |
| User interaction | None |
| EPSS exploit chance | 0.4% (top 66%) |
| CISA exploited list | No |
| Weakness | CWE-120 |
| Published | 2021-12-17 |
| Last modified | 2026-06-17 |
Last updated 2026-06-17 · Sources: CVE Program, NVD, CISA KEV, EPSS and vendor advisories · How we score
Am I affected?
Timeline
- Published CVE record published
- Updated Record last modified
Scores and fixes here are computed automatically from those and other public sources. Confirm with the vendor advisory before changing production systems.
Quick answers
How do I fix CVE-2021-41496?
numpy: upgrade to 1.19.0. Exact commands for each OS are on this page.
Is CVE-2021-41496 being exploited?
CVE-2021-41496 is not on the CISA Known Exploited Vulnerabilities list at the time of the last update. Check again, as this can change.
What does CVE-2021-41496 affect?
CVE-2021-41496 affects numpy. Severity is medium (CVSS 5.5). 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
How urgent is CVE-2021-41496?
Priority 33/100. Public exploit reference
Software pages
Pandas and NumPy vulnerabilities
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