GHSA-h5cg-53g7-gqjw is a high-severity (CVSS 8.5) Missing Authentication vulnerability in rpyc. A fix is available for rpyc — see the affected versions and patch details below.
RPyC's missing security check results in code execution when using numpy.array on the server-side.
Exploitation Status
Proof-of-concept exploit code exists
- CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
- A successful exploit gives an attacker total control of the affected component, not partial access.
Exploitation and automatability from CISA’s SSVC triage for GHSA-h5cg-53g7-gqjw.
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-h5cg-53g7-gqjw 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 379,145 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
rpycReal-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 issue in Open Source: RPyC v.4.00 thru v.5.3.1 allows a remote attacker to execute arbitrary code via a crafted script to the __array__ attribute component. This vulnerability was introduced in 9f45f826.
Attack Vector
RPyC services that rely on the __array__ attribute used by numpy are impacted. When the server-side exposes a method that calls the attribute named __array__ for a a client provided netref (e.g., np.array(client_netref)), a remote attacker can craft a class which results in remote code execution
Impact
Assuming the system exposes a method that calls the attribute __array__, an attacker can execute code using the vulnerable component.
Patches
The fix is available in RPyC 6.0.0. The major version change is because some users may need to set allow_pickle to True when migrating to RPyC 6.
Workarounds
While the recommend fix is to upgrade to RPyC 6.0.0, the workaround is to apply bba1d356 as patch.
Affected Component
The affected component is the __array__ method constructed for NetrefClass.
References
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | rpyc | ≥ 4.0.0&&< 6.0.0 | 6.0.0pip install --upgrade 'rpyc==6.0.0' |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for rpyc, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update rpyc to 6.0.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-h5cg-53g7-gqjw 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-h5cg-53g7-gqjw can be triaged on real exposure rather than presence alone.
Tailored to GHSA-h5cg-53g7-gqjw. 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-h5cg-53g7-gqjw in your dependencies?
O3 Security finds GHSA-h5cg-53g7-gqjw across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.