How severe is CVE-2024-27758?

CVE-2024-27758 has a CVSS score of 8.4/10, rated HIGH. Immediate patching is strongly recommended.

Which packages are affected by CVE-2024-27758?

CVE-2024-27758 affects the following packages: rpyc (PyPI). Ecosystems affected: PyPI.

How do I fix CVE-2024-27758?

Update rpyc to 6.0.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2024-27758 is resolved across your whole dependency graph.

How do I detect CVE-2024-27758 in my PyPI dependencies?

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.

How do I mitigate CVE-2024-27758 if there is no patch (or I can't update yet)?

Put an independent control in front of the weakness: restrict the affected endpoint or interface to trusted networks, require an additional authentication factor or proxy-level check, and invalidate existing sessions and credentials in case the flaw has already been used.

Is CVE-2024-27758 actively exploited in the wild?

No public exploit code has been indexed for CVE-2024-27758 yet. This does not mean the vulnerability cannot be exploited — absence of public exploits does not imply safety. Apply the recommended fix and use O3 Security to monitor your exposure.

What is the EPSS score for CVE-2024-27758?

CVE-2024-27758 has an EPSS (Exploit Prediction Scoring System) score of 0.5%, placing it in the 43th percentile of all CVEs. EPSS is maintained by FIRST.org and estimates the probability that a vulnerability will be exploited in the wild within the next 30 days. This score indicates relatively lower exploitation probability, though the CVSS severity should still guide your patching priority.

What type of vulnerability is CVE-2024-27758?

CVE-2024-27758 is classified as Missing Authentication (CWE-306). This weakness type describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation.

When was CVE-2024-27758 published, and has it been updated?

CVE-2024-27758 was published on March 12, 2024 and was last updated on October 28, 2026. Advisory data evolves as severity scores, affected ranges, and exploit intelligence are revised — always check the latest version of the advisory before acting.

🐍

🐍 PyPI

Not in CISA KEV

HIGH severity

CVE-2024-27758 — rpyc

HIGHFix: tomerfiliba-org/rpyc@9f45f82

CVE-2024-27758 is a high-severity (CVSS 8.4) 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.

Also known asGHSA-h5cg-53g7-gqjwPYSEC-2024-44

Published

Mar 12, 2024

Updated

Oct 28, 2026

Affected

1 pkg

Patched

1 / 1

Exploits

None indexed

Exploitation data as of Nov 6, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

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 CVE-2024-27758.

EPSS Exploitation Probability

via FIRST.org ↗

0.5%probability of exploitation in next 30 days

Lower Risk0.00%

Lower risk than most CVEs43th percentile — riskier than 43% of all scored CVEsHighest risk

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

1 pkg affected

🐍rpyc

Real-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

1 total 1 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`rpyc`	≥ 4.0.0&&< 6.0.0	6.0.0`pip install --upgrade 'rpyc==6.0.0'`

Detection & mitigation playbook

Open-source dependency

Detect
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 CVE-2024-27758 is resolved across your whole dependency graph.
Workarounds
Put an independent control in front of the weakness: restrict the affected endpoint or interface to trusted networks, require an additional authentication factor or proxy-level check, and invalidate existing sessions and credentials in case the flaw has already been used.

Frequently Asked Questions

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](https://github.com/tomerfiliba-org/rpyc/commit/9f45f8269d4106905db61d82cd529cacdb178911). ### 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