CVE-2026-48891
Summary
by MITRE • 07/07/2026
A bug in Apache Airflow's `/ui/dependencies` scheduling graph endpoint applied the caller's readable-Dag filter to the top-level serialized Dag key but still emitted referenced Dag IDs through the `dep.source` and `dep.target` fields of trigger / sensor dependency entries. An authenticated UI user with read permission on some Dags could enumerate the identifiers of other Dags they were not authorized to read by inspecting the dependency graph for trigger / sensor references. Affects deployments that rely on per-Dag read scoping to keep Dag identifiers private across teams. This is a residual gap in the fix for CVE-2026-28563, which filtered the top-level Dag key but did not propagate the filter into the trigger / sensor dep-source / dep-target fields. Users who already upgraded for CVE-2026-28563 should additionally upgrade to `apache-airflow` 3.3.0 or later to cover the residual trigger / sensor dependency leak.
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Analysis
by VulDB Data Team • 07/07/2026
This vulnerability represents a privilege escalation and information disclosure issue within Apache Airflow's user interface that stems from an incomplete fix for a previously identified security flaw. The core problem manifests in the `/ui/dependencies` endpoint which is responsible for rendering scheduling graphs that display trigger and sensor dependencies between different DAGs. The system correctly implements filtering for the top-level serialized DAG key to respect user permissions, but fails to apply the same authorization checks to the dependency source and target fields within trigger and sensor references. This creates a situation where authenticated users with read access to specific DAGs can indirectly discover identifiers of other DAGs they should not be able to access by examining the dependency graph structure.
The technical flaw operates through a classic information leakage pattern where permission boundaries are not consistently enforced across all data elements within a system. When an authenticated user requests the dependencies for a DAG they have read access to, the system correctly filters out DAG identifiers that the user should not see from the main serialized DAG key. However, the dependency entries that reference other DAGs through the `dep.source` and `dep.target` fields remain unfiltered, allowing attackers to enumerate DAG identifiers by inspecting these references. This represents a failure in the principle of least privilege implementation where authorization checks are not uniformly applied throughout the data structure.
The operational impact of this vulnerability is significant for organizations that rely on per-DAG read scoping as a security control mechanism to maintain privacy between different teams or departments working within the same Airflow deployment. Teams can inadvertently expose their DAG identifiers to unauthorized users who have access to other DAGs, potentially revealing sensitive information about workflow architectures, business processes, or system dependencies. This enumeration capability could enable attackers to craft more targeted attacks or gather intelligence about the organization's data processing infrastructure. The vulnerability particularly affects deployments where DAG identifiers contain meaningful information about the workflows they represent, making it easier for unauthorized parties to understand and potentially exploit the system.
Organizations should immediately upgrade to Apache Airflow version 3.3.0 or later to address this residual gap in the previous fix for CVE-2026-28563. The mitigation requires a complete reevaluation of authorization controls within the UI dependency graph rendering logic to ensure that all references to DAG identifiers are properly filtered according to user permissions. This vulnerability aligns with CWE-284 (Improper Access Control) and could be categorized under ATT&CK technique T1068 (Exploitation for Privilege Escalation) when exploited by attackers seeking to expand their access. The fix demonstrates the importance of comprehensive security testing that covers all data pathways within a system rather than focusing on single attack vectors, as the previous fix addressed only part of the authorization gap while leaving other components vulnerable to similar enumeration attacks.
This issue highlights the complexity of implementing proper access controls in distributed systems where multiple data structures and relationships need to be consistently protected. The vulnerability serves as a reminder that security fixes must be thorough and validated across all affected code paths, particularly in user interface components that aggregate and display information from multiple sources. Organizations should conduct comprehensive audits of their Airflow deployments to ensure no other similar authorization gaps exist within the system's dependency resolution or graph visualization features.