CVE-2026-34984 (GCVE-0-2026-34984)
Vulnerability from cvelistv5 – Published: 2026-04-14 01:48 – Updated: 2026-04-14 16:27
VLAI
EPSS
VEX
Title
External Secrets Operator has DNS exfiltration via getHostByName in its v2 template engine
Summary
External Secrets Operator reads information from a third-party service and automatically injects the values as Kubernetes Secrets. Versions 2.2.0 and below contain a vulnerability in runtime/template/v2/template.go where the v2 template engine removes env and expandenv from Sprig's TxtFuncMap() but leaves the getHostByName function accessible to user-controlled templates. Since ESO executes templates within the controller process, an attacker who can create or update templated ExternalSecret resources can invoke controller-side DNS lookups using secret-derived values. This creates a DNS exfiltration primitive, allowing fetched secret material to be leaked via DNS queries without requiring direct outbound network access from the attacker's workload. The impact is a confidentiality issue, particularly in environments where untrusted or lower-trust users can author templated ExternalSecret resources and the controller has DNS resolution capability. This issue has been fixed in version 2.3.0.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-04-14 15:37 UTC
CWE
- CWE-200 - Exposure of Sensitive Information to an Unauthorized Actor
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/external-secrets/external-secr… | x_refsource_CONFIRM |
| https://github.com/external-secrets/external-secr… | x_refsource_MISC |
| https://github.com/external-secrets/external-secr… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| external-secrets | external-secrets |
Affected:
< 2.3.0
|
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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