CVE-2026-49487 in Airflow
Summary
by MITRE • 07/07/2026
In Apache Airflow before 3.3.0, the REST API task-instance detail and list endpoints returned a deferred task's trigger kwargs without masking. When a deferred operator passed a secret (for example a provider API key) into its trigger, any authenticated user with DAG-scoped task-instance read access for that DAG could read that secret in clear text while the task was deferred. Users should upgrade to apache-airflow 3.3.0 or later, which masks sensitive values in trigger kwargs returned by the API.
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Analysis
by VulDB Data Team • 07/07/2026
This vulnerability exists within Apache Airflow's REST API implementation prior to version 3.3.0, specifically affecting the task-instance detail and list endpoints. The flaw represents a critical information disclosure issue where sensitive data passed through deferred tasks is exposed without proper masking mechanisms. When operators utilize deferred execution patterns and pass authentication credentials or other secrets as trigger arguments, these values remain visible in clear text within API responses. This exposure occurs regardless of the user's role within the system, as long as they possess DAG-scoped task-instance read permissions for the affected DAG. The vulnerability directly impacts the principle of least privilege by allowing unauthorized data access through legitimate API pathways that should only expose non-sensitive operational information.
The technical implementation flaw stems from insufficient sanitization of trigger kwargs within the REST API response handling for deferred tasks. When a task enters a deferred state, its trigger parameters are stored and subsequently returned by the API endpoints without proper redaction or masking of sensitive fields. This behavior violates fundamental security principles around data protection and demonstrates inadequate input validation within the API layer. The vulnerability is particularly dangerous because it leverages existing legitimate access patterns rather than requiring additional privilege escalation. Attackers can exploit this through standard authenticated API calls, making detection more challenging as the activity appears normal within the system's operational workflow.
The operational impact of this vulnerability extends beyond simple information disclosure to potentially compromise entire infrastructure security postures. When API keys, database credentials, or other sensitive tokens are passed as trigger arguments, their exposure creates immediate risk for unauthorized access to external systems and services. This vulnerability affects the confidentiality aspect of the CIA triad by enabling unauthorized data reading through legitimate system interfaces. Organizations using Apache Airflow with deferred operators may unknowingly expose production secrets during task execution phases, particularly when tasks remain in deferred states for extended periods. The risk is compounded because the exposure occurs at the API level rather than within application code, making it harder to detect through traditional code analysis approaches.
Organizations should immediately upgrade to Apache Airflow version 3.3.0 or later to address this vulnerability, as this release implements proper masking of sensitive values within trigger kwargs returned by the API endpoints. The fix aligns with security best practices outlined in CWE-200, which addresses information exposure through improper data handling. Additionally, this remediation addresses ATT&CK technique T1528, which focuses on bypassing system restrictions to access sensitive data. Security teams should also implement monitoring for API calls that access task-instance endpoints, particularly when these queries involve deferred tasks, to detect potential exploitation attempts. Organizations should conduct comprehensive audits of their deferred operator implementations to identify any instances where secrets might be passed through trigger parameters and ensure proper credential management practices are implemented throughout their workflow definitions.