CVE-2026-45426

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.

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.

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.