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CVE-2026-48892 is an information disclosure vulnerability in the Apache Airflow Config API that causes plaintext secrets-backend credentials to be exposed to authenticated users. The vulnerability affects all versions of Apache Airflow before 3.3.0. It was disclosed on July 7, 2026, by the Apache Software Foundation, with the fix merged on May 27, 2026, and included in the 3.3.0 release. The CVSS v3.1 base score is 6.5 (Medium) (Apache Advisory, GitHub Advisory).
The root cause is classified as CWE-200 (Exposure of Sensitive Information to an Unauthorized Actor). When secrets backends are configured via per-key environment variable overrides (e.g., AIRFLOW__SECRETS__BACKEND_KWARG__SECRET_ID, AIRFLOW__WORKERS__SECRETS_BACKEND_KWARG__SECRET_ID), Airflow's conf.as_dict() materializes these as synthetic config options under the secrets and workers sections (e.g., backend_kwarg__secret_id). Because these synthetic option names were not registered in conf.sensitive_config_values, the masking mechanism did not redact them, and the GET /config and GET /config/section/{section}/option/{option} API routes returned their values in plaintext. Exploitation requires only a valid Airflow account with Config read permission and network access to the API (GitHub PR, oss-security).
An authenticated user with Config read permission can retrieve plaintext secrets-backend credentials — such as HashiCorp Vault role_id and secret_id — directly from the Config API response. Exposure of these credentials could allow an attacker to authenticate to the secrets backend independently, potentially accessing all secrets managed by that backend (e.g., database passwords, API keys, cloud credentials). This creates a significant risk of lateral movement and privilege escalation beyond the Airflow environment itself, depending on what secrets are stored in the backend (GitHub Advisory, oss-security).
AIRFLOW__SECRETS__BACKEND_KWARG__SECRET_ID.Config read permission (a relatively common permission in multi-user deployments).GET /api/v1/config
Authorization: Bearer <token>or target a specific option:GET /api/v1/config/section/secrets/option/backend_kwarg__secret_idsecrets or workers sections (e.g., backend_kwarg__secret_id, backend_kwarg__role_id). These values are returned unmasked in plaintext.role_id and secret_id (or equivalent) to authenticate directly to the secrets backend and access all managed secrets (GitHub PR, oss-security)./api/v1/config or /api/v1/config/section/secrets/option/backend_kwarg__* from unexpected source IPs or user accounts; API calls to the secrets backend (e.g., Vault) using credentials that match those stored in Airflow environment variables, originating from non-Airflow infrastructure.GET /api/v1/config requests by accounts that do not normally access configuration endpoints; Vault audit logs showing role_id/secret_id authentication attempts from unexpected clients or IP addresses.The primary remediation is to upgrade Apache Airflow to version 3.3.0 or later, which adds proper masking of per-key secrets-backend kwarg synthetic config options via the _PER_KEY_SENSITIVE_PREFIXES constant and associated helpers (GitHub PR, Apache Advisory). As an interim workaround, administrators should restrict the Config read permission to only those users who strictly require it, minimizing the number of accounts that can access the Config API. Additionally, organizations should audit their Airflow deployments to determine if any unauthorized access to the Config API has occurred, and consider rotating secrets-backend credentials (e.g., Vault role_id/secret_id) if exposure is suspected.
The vulnerability was disclosed via the Apache security mailing list and oss-security on July 7, 2026, and received standard coverage across CVE tracking platforms. Social media activity was limited to automated CVE notification accounts on Bluesky. No significant vendor statements beyond the official advisory or notable independent researcher commentary have been identified beyond the finder credit given to Omkhar Arasaratnam (@omkhar) (oss-security).
Source: This report was generated using AI
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