GHSA-frgw-fgh6-9g52 — numpy
HIGHGHSA-frgw-fgh6-9g52 is a high-severity (CVSS 7.5) CWE-835 vulnerability in numpy. 1 public exploit reference exists, so weaponization risk is real. A fix is available for numpy — see the affected versions and patch details below.
Numpy missing input validation
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
How urgent is this, really
GHSA-frgw-fgh6-9g52 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.
Where this sits among everything scored
Of 377,166 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.
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
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.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | numpy | all versions | 1.13.3pip install --upgrade 'numpy==1.13.3' |
Research 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 1.13.3 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-frgw-fgh6-9g52 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.
How O3 protects you
O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-frgw-fgh6-9g52 can be triaged on real exposure rather than presence alone.
Tailored to GHSA-frgw-fgh6-9g52. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-frgw-fgh6-9g52 in your dependencies?
O3 Security finds GHSA-frgw-fgh6-9g52 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.