The structuredata endpoint in the Airflow UI returned external dependency graph nodes for linked Dags without checking whether the caller had read permission on those linked Dags. An authenticated UI/API user authorized for one Dag could enumerate linked Dag IDs and dependency metadata for other Dags they were not authorized to read. Affects deployments that rely on per-Dag read scoping to keep Dag dependency topology private across teams. Users are advised to upgrade to apache-airflow 3.2.2 or later.

Exploitation requires the attacker to already be an authenticated Airflow worker holding a valid Log-server JWT issued for at least one Dag. Apache Airflow's Log server authorized JWT tokens against Dag IDs by applying Python's str.lstrip() to the requested path segment when verifying the JWT's sub claim. str.lstrip() strips any of a set of characters from the left (not a prefix), so a JWT issued for a Dag named e.g. daga would authorize log access to any other Dag whose name began with any subset of the characters {d, a, g, } (e.g. dagattacker, aaaatarget, dagsecret). Such an authenticated worker could enumerate and read worker logs of other Dags whose names happened to share that character-class prefix, leaking task output and error traces beyond the documented per-Dag isolation boundary. Affects deployments relying on per-Dag log-access scoping (multi-team, shared-executor, shared-worker topologies). Users are advised to upgrade to apache-airflow 3.2.2 or later.

Secrets in Variables saved as JSON dictionaries were not properly redacted - in case the variables were retrieved by the user the secrets stored as nested fields were not masked.

If developers do not store variables with sensitive values in JSON form, their projects are not affected. Otherwise upgrade to the fixed version, Apache Airflow 3.2.0.