Incorrect Comparison in NumPyGHSA-fpfv-jqm9-f5jm
MEDIUMGHSA-fpfv-jqm9-f5jm is a medium-severity (CVSS 5.3) CWE-697 vulnerability in numpy. 1 public exploit or proof-of-concept reference is indexed, so weaponization risk is real. A fix is available for numpy — see the affected versions and patch details below.
Exploitation Status
No confirmed exploitation observed yet
- CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
- CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.
Exploitation and automatability from CISA’s SSVC triage for GHSA-fpfv-jqm9-f5jm.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
How urgent is this, really
Where this sits among everything scored
Real-World Exposure
numpyReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. NOTE: the vendor states that this reported code behavior is "completely harmless."
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | numpy | all versions | 1.22pip install --upgrade 'numpy==1.22' |
Affected Products
numpynumpycommunications cloud native core policyoracleResearch use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for numpy, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update numpy to 1.22 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-fpfv-jqm9-f5jm is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
Frequently Asked Questions
Is GHSA-fpfv-jqm9-f5jm in your dependencies?
Find it across PyPI, including transitive dependencies.