CVE-2024-56513 (GCVE-0-2024-56513)
Vulnerability from cvelistv5 – Published: 2025-01-03 16:11 – Updated: 2025-01-03 17:22
VLAI
EPSS
VEX
Title
Karmada PULL Mode Cluster Privilege Escalation
Summary
Karmada is a Kubernetes management system that allows users to run cloud-native applications across multiple Kubernetes clusters and clouds. Prior to version 1.12.0, the PULL mode clusters registered with the `karmadactl register` command have excessive privileges to access control plane resources. By abusing these permissions, an attacker able to authenticate as the karmada-agent to a karmada cluster would be able to obtain administrative privileges over the entire federation system including all registered member clusters. Since Karmada v1.12.0, command `karmadactl register` restricts the access permissions of pull mode member clusters to control plane resources. This way, an attacker able to authenticate as the karmada-agent cannot control other member clusters in Karmada. As a workaround, one may restrict the access permissions of pull mode member clusters to control plane resources according to Karmada Component Permissions Docs.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-01-03 17:21 UTC
CWE
- CWE-266 - Incorrect Privilege Assignment
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/karmada-io/karmada/security/ad… | x_refsource_CONFIRM |
| https://github.com/karmada-io/karmada/pull/5793 | x_refsource_MISC |
| https://github.com/karmada-io/karmada/commit/2c82… | x_refsource_MISC |
| https://karmada.io/docs/administrator/security/co… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| karmada-io | karmada |
Affected:
< 1.12.0
|
guessed |
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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
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