CVE-2026-52724 (GCVE-0-2026-52724)
Vulnerability from cvelistv5 – Published: 2026-09-15 14:50 – Updated: 2026-09-15 15:21
VLAI
EPSS
VEX
Title
kuma-dp connects to control plane without verifying TLS certificate when no CA is configured
Summary
Kuma is a modern Envoy-based service mesh that can run on every cloud across both Kubernetes and VMs. Prior to 2.7.26, 2.9.16, 2.11.14, 2.12.11, and 2.13.7, Universal mode kuma-dp connections to an HTTPS control plane disable TLS peer verification when --ca-cert-file is not supplied and KUMA_CONTROL_PLANE_CA_CERT is unset. The dataplane authentication token is sent over the unverified connection, allowing an on-path attacker to intercept the token, impersonate the control plane, inject a forged bootstrap configuration, and take over the proxy. Standard Kubernetes installations created by kumactl install control-plane or the official Helm chart are unaffected because the mutating admission webhook injects KUMA_CONTROL_PLANE_CA_CERT into each sidecar. This issue is fixed in versions 2.7.26, 2.9.16, 2.11.14, 2.12.11, and 2.13.7.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-15 15:20 UTC
CWE
- CWE-295 - Improper Certificate Validation
Assigner
References
8 references
| URL | Tags |
|---|---|
| https://github.com/kumahq/kuma/security/advisorie… | x_refsource_CONFIRM |
| https://github.com/kumahq/kuma/pull/16777 | x_refsource_MISC |
| https://github.com/kumahq/kuma/commit/2d0fb382924… | x_refsource_MISC |
| https://github.com/kumahq/kuma/commit/85716397ffa… | x_refsource_MISC |
| https://github.com/kumahq/kuma/commit/a256af4869a… | x_refsource_MISC |
| https://github.com/kumahq/kuma/commit/bb56ae62875… | x_refsource_MISC |
| https://github.com/kumahq/kuma/commit/d4ae0c01515… | x_refsource_MISC |
| https://github.com/kumahq/kuma/commit/eb81494c2c7… | x_refsource_MISC |
Impacted products
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"discovery": "UNKNOWN"
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"title": "kuma-dp connects to control plane without verifying TLS certificate when no CA is configured"
}
},
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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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