A Dag author could either (a) create a symlink under their task's log directory pointing to an arbitrary file readable by the API server process (read-path attack — e.g. `/etc/passwd` or `airflow.cfg`) or (b) supply a `task_id` containing `..` sequences accepted by the Task SDK's `KEY_REGEX` (write-path attack), and in both cases the FileTaskHandler resolves the log path outside the configured `base_log_folder`, leaking or overwriting arbitrary files. Only affects deployments where the worker log folder is shared with the API server. Users are advised to upgrade to `apache-airflow` 3.2.2 or later. As a defense-in-depth mitigation, deploy the worker and API server with separate log volumes so that worker-controlled paths cannot reach the API server's filesystem.

A bug in Apache Airflow's bulk Task Instances API (`PATCH/DELETE /api/v2/dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances`) evaluated authorization against the `dag_id` resolved from the URL path while operating on the `dag_id` / `dag_run_id` extracted from request-body entity fields. An authenticated UI/API user with edit permission on one Dag could mutate Task Instance state in any other Dag by keeping the authorized Dag's ID in the URL path and naming the target Dag's IDs in the request body entities. Affects deployments that rely on per-Dag edit-scope to keep Task Instance state isolated between teams. Users are advised to upgrade to `apache-airflow` 3.2.2 or later.

Apache Airflow's `JWTRefreshMiddleware` set the JWT auth cookie without the `Secure` flag, so deployments running the Airflow API server behind an HTTPS-terminating reverse proxy (e.g. nginx / Envoy / a managed load balancer that terminates TLS and forwards plaintext to the API server, the default cloud-native topology) would have the user's session JWT replayed over any cleartext HTTP request to the same host. A network-positioned attacker (Wi-Fi MITM, hostile LAN, captive-portal proxy) could induce a logged-in user's browser to issue an HTTP request to the deployment's hostname and capture the JWT cookie out of that request, then replay it against the authenticated API. Affects deployments where the Airflow API server is reached through a TLS-terminating proxy and the cookie's secure-by-default protection is load-bearing for session integrity. 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.

A bug in Apache Airflow's KubernetesExecutor caused JWT tokens used by worker pods to authenticate against the Execution API to be passed to the worker container as command-line arguments visible in the pod spec. An authenticated UI/API user with Kubernetes read-only access to the cluster (e.g. `pods/get` in the Airflow namespace) could harvest the JWT from `kubectl describe pod` output and then call state-mutating Execution API endpoints — triggering Dag runs, clearing runs, reading or writing Variables / Connections / XComs — as if they were a running task. Affects deployments using the `KubernetesExecutor`. Users are advised to upgrade to `apache-airflow` 3.2.2 or later. This is the airflow-core half of the same vulnerability addressed by [CVE-2026-27173](https://www.cve.org/CVERecord?id=CVE-2026-27173), which shipped the apache-airflow-providers-cncf-kubernetes side of the fix. Deployments that already upgraded `apache-airflow-providers-cncf-kubernetes` to 10.17.0 or later per the CVE-2026-27173 advisory should additionally upgrade `apache-airflow` to 3.2.2 or later to close the core-side surface — the two fixes are complementary, not duplicates.

The asset dependency graph did not restrict nodes by the viewer's DAG read permissions: a user with read access to at least one DAG could browse the asset graph for any other asset in the deployment and learn the existence and names of DAGs and assets outside their authorized scope. Users are recommended to upgrade to version 3.2.1, which fixes this issue.

The authenticated /ui/dags endpoint did not enforce per-DAG access control on embedded Human-in-the-Loop (HITL) and TaskInstance records: a logged-in Airflow user with read access to at least one DAG could retrieve HITL prompts (including their request parameters) and full TaskInstance details for DAGs outside their authorized scope. Because HITL prompts and TaskInstance fields routinely carry operator parameters and free-form context attached to a task, the leak widens visibility of DAG-run data beyond the intended per-DAG RBAC boundary for every authenticated user. Users are recommended to upgrade to version 3.2.1 , which fixes this issue.

UI / API User with asset materialize permission could trigger dags they had no access to. Users are advised to migrate to Airflow version 3.2.0 that fixes the issue.

Secrets in Variables saved as JSON dictionaries were not properly redacted - in case thee variables were retrieved by the user the secrets stored as nested fields were not masked. If you do not store variables with sensitive values in JSON form, you are not affected. Otherwise please upgrade to Apache Airflow 3.2.0 that has the fix implemented

Dag Authors, who normally should not be able to execute code in the webserver context could craft XCom payload causing the webserver to execute arbitrary code. Since Dag Authors are already highly trusted, severity of this issue is Low. Users are recommended to upgrade to Apache Airflow 3.2.0, which fixes the issue.