CVE-2026-59244 (GCVE-0-2026-59244)
Vulnerability from cvelistv5 – Published: 2026-08-12 15:43 – Updated: 2026-08-12 17:20
VLAI
EPSS
VEX
Title
Apache Airflow: Secrets masker: `var.json` Variable values not masked in the Rendered Templates UI
Summary
Apache Airflow's secrets masker did not mask `var.json` Variable values whose value is a dict in the Rendered Templates UI — the dict value failed an `isinstance(str)` guard — so a secret stored as a JSON Variable and referenced in a template via `var.json` was displayed in cleartext to any user with access to that task's Rendered Templates view. Users are advised to upgrade to apache-airflow 3.3.1 or later, which masks nested Variable values regardless of type.
Severity
No CVSS data available.
CWE
- CWE-312 - Cleartext Storage of Sensitive Information
Assigner
References
3 references
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| Apache Software Foundation | Apache Airflow |
Affected:
0 , < 3.3.1
(semver)
|
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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.
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.
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