CVE-2026-45426

Ein Angreifer kann mehrere Schwachstellen in Apache Airflow ausnutzen, um beliebigen Programmcode auszuführen, um Informationen offenzulegen, um Dateien zu manipulieren, und um Sicherheitsvorkehrungen zu umgehen.

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. `dag_a` would authorize log access to any other Dag whose name began with any subset of the characters `{d, a, g, _}` (e.g. `dag_attacker`, `aaaa_target`, `_dag_secret`). 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.

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. `dag_a` would authorize log access to any other Dag whose name began with any subset of the characters `{d, a, g, _}` (e.g. `dag_attacker`, `aaaa_target`, `_dag_secret`). 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.

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. `dag_a` would authorize log access to any other Dag whose name began with any subset of the characters `{d, a, g, _}` (e.g. `dag_attacker`, `aaaa_target`, `_dag_secret`). 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.