CVE-2024-27758 (GCVE-0-2024-27758)
Vulnerability from cvelistv5 – Published: 2024-03-12 00:00 – Updated: 2024-08-02 00:34
VLAI
EPSS
VEX
Summary
In RPyC before 6.0.0, when a server exposes a method that calls the attribute named __array__ for a client-provided netref (e.g., np.array(client_netref)), a remote attacker can craft a class that results in remote code execution.
Severity
8.4 (High)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-07-25 19:53 UTC
CWE
- n/a
- CWE-306 - Missing Authentication for Critical Function
Assigner
References
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| rpyc_project | rpyc |
Affected:
0 , < 6.0.0
(custom)
cpe:2.3:a:rpyc_project:rpyc:*:*:*:*:*:*:*:* |
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"cna": {
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"dateReserved": "2024-02-26T00:00:00.000Z",
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}
],
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"lastModified": "2024-11-21T09:05:00.297",
"metrics": {
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},
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}
],
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"lastModified": "2026-06-17T07:20:14.820",
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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