| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| Apache Airflow's Task Execution API stored XCom values written by a task without the reserved-key check applied elsewhere, so a Dag author's task could write an XCom that, when a user later viewed it through the API with deserialization enabled, made the API server instantiate classes from the `airflow.*` namespace with arguments the Dag author chose. This is an incomplete fix for CVE-2026-59242: users who applied that fix in apache-airflow 3.3.1 remain affected through this route and should upgrade to apache-airflow 3.4.0 or later. |
| Apache Airflow's API endpoint for deleting an asset's queued events checked Dag edit permission against the `dag_id` query parameter, but deleted the queued events of every Dag the caller could read. An authenticated user with edit permission on one Dag and read access to others could suppress asset-triggered runs of Dags they cannot edit. This is an incomplete fix for CVE-2026-75157: users who upgraded to apache-airflow 3.3.2 for that fix are still affected and should upgrade to apache-airflow 3.4.0 or later. |
| Apache Airflow's CeleryExecutor ran callback workloads (`ExecuteCallback`, used for deadline-alert callbacks) without validating the workload's authentication token. Anyone able to write to the Celery broker could enqueue a forged callback and execute arbitrary code on every CeleryExecutor worker, without Airflow credentials. Deployments using the CeleryExecutor are affected.
Users are advised to upgrade to apache-airflow 3.4.0 or later, in which the worker claims the callback through the Execution API, validating the token, before running it. |
| Apache Airflow's asset API endpoints returned the IDs of Dags that are scheduled on, produce, or consume an asset without checking whether the caller may read those Dags. An authenticated user with asset read access could learn the IDs of Dags they are not authorized to see. Users are advised to upgrade to apache-airflow 3.4.0 or later. Airflow 2.x is also affected; Airflow 2 has reached end of life and will not receive a fix, so Airflow 2 users should upgrade to Apache Airflow 3.4.0 or later. |
| Apache Airflow's secrets masker matched sensitive key names only in their snake_case form, so values stored under camelCase keys such as `privateKey`, `connectionString`, `webhookUrl` or `accessKey` — for example in a Connection's extra or a Variable — were not redacted in task logs, rendered template fields or API responses. A user who can read task logs or rendered templates, but is not meant to see those credentials, could read them in cleartext. Users are advised to upgrade to apache-airflow 3.4.0 or later. Airflow 2.x is also affected; Airflow 2 has reached end of life and will not receive a fix, so Airflow 2 users should upgrade to Apache Airflow 3.4.0 or later. |
| The Apache Airflow connections API did not mask the apprise provider's `config` connection extra, which can embed notification-service credentials. A user with permission to read connections could retrieve it in cleartext, although Airflow 3 treats connection credentials as write-only.
Users are advised to upgrade to apache-airflow 3.4.0 or later. Airflow 2.x is also affected; Airflow 2 has reached end of life and will not receive a fix, so Airflow 2 users should upgrade to Apache Airflow 3.4.0 or later. |
| Apache Airflow's CLI records its arguments in the audit log but masks secrets by argument position, so some supported command shapes leave secrets in cleartext, for example a trailing `--description` on Variable commands, `--conn-extra`, and the inline `--password` of `airflow keycloak-auth-manager` commands. A user who can read audit events but is denied Variable and Connection access can retrieve those values through the event-log API.
Users of apache-airflow are recommended to upgrade to 3.4.0 or later. Audit-log entries written before the upgrade keep the cleartext values: purge the affected entries and rotate the secrets they contain. Airflow 2.x is also affected; Airflow 2 has reached end of life and will not receive a fix, so Airflow 2 users should upgrade to Apache Airflow 3.4.0 or later. |
| Apache Airflow's secrets masker stopped descending into nested structures after five levels, so a secret registered with the masker — for example a Connection password or a Variable value — that appeared more than five containers deep under non-sensitive keys was shown in cleartext in task logs and rendered template fields. A user who can read task logs or rendered templates, but is not meant to see those secrets, could read them. Users are advised to upgrade to apache-airflow 3.4.0 or later. Airflow 2.x is also affected; Airflow 2 has reached end of life and will not receive a fix, so Airflow 2 users should upgrade to Apache Airflow 3.4.0 or later. |
| Apache Airflow's audit log stored Connection and Variable secret values in cleartext in the `Log.extra` column because the secrets masker matched only on configured sensitive key names. An authenticated low-privilege user with read access to the event-log / audit API — with no prior access to the affected connection or variable — could read those rows and recover the credentials verbatim. Users should upgrade to apache-airflow 3.4.0 or later, which masks these values and restricts the affected audit rows to authorized users. Airflow 2.x is also affected; Airflow 2 has reached end of life and will not receive a fix, so Airflow 2 users should upgrade to Apache Airflow 3.4.0 or later. |
| Apache Airflow's public Import Errors API returns the raw parse-failure stack trace to any user with the `ImportError.can_read` permission when the failing file has no registered DAG. This happens when a file fails to parse before any DAG is defined, or when all of its previously registered DAGs are removed but the parse error remains. Users who should not see that file's details can read stack traces that may expose file paths and code.
Users are advised to upgrade to Apache Airflow 3.4.0 or later, which restricts these stack traces to users with the new `IMPORT_ERRORS_ALL` permission. |
| The `example_dag_decorator` example Dag shipped with Apache Airflow validated an IP address fetched over HTTP with Python's `ipaddress` module and then placed it into a shell command. `ipaddress` accepts IPv6 zone identifiers containing arbitrary characters, so when example Dags are loaded (`load_examples` enabled), a user who can trigger that Dag with a custom `url` parameter could point it at a server whose response injects shell commands run on the worker. This is an incomplete fix for CVE-2025-54941; users who upgraded for CVE-2025-54941 should upgrade again. Users are advised to upgrade to apache-airflow 3.4.0 or later, or to disable example Dags (`load_examples = False`), which is recommended for production. |
| Apache Airflow's logout endpoint attempted to revoke the presented token on the server, but any failure during revocation was silently ignored and logout still reported success. When the auth manager redirects logout to an external logout URL (for example the FAB or Keycloak auth managers), server-side revocation is the only thing that invalidates the Airflow token; it failed on database errors and, reliably, for tokens from an external issuer accepted via `[api_auth] trusted_jwks_url` whose token identifier is longer than 32 characters. Anyone holding a copy of a user's token from before logout could keep using it against the Airflow API until it expired. Users are advised to upgrade to apache-airflow 3.4.0 or later. |
| Apache Airflow 3.3.1 shipped a fix for CVE-2026-67260 that checks the scheduler's decoded `next_kwargs` value is a dictionary, but performs that check only after deserializing the whole stored payload. Deserialization reconstructs nested objects of classes permitted by the deserialization allow-list — which by default includes Airflow's own classes — and runs their constructors inside the scheduler process before the check can reject the value. A Dag author, who controls a task's `next_kwargs` through the task execution API, can therefore still trigger constructor execution in the scheduler when the `awaiting_input` timeout sweep processes the task, and in the API server when the task instance is served to a worker using an older Execution API version; no non-default configuration is required. Versions before 3.3.0 are not affected. This is an incomplete fix for CVE-2026-67260: deployments that upgraded to 3.3.1 for that issue must also upgrade to apache-airflow 3.4.0 or later. |
| Apache Airflow rebuilt deadline alert fields through generic deserialization, which imports and instantiates the class named in the serialized Dag, in the scheduler and API server. A Dag author could cause classes within Airflow's deserialization allow list to be constructed in those processes with arguments they control. Deployments whose Dags use deadline alerts are affected.
This is an incomplete fix of CVE-2026-45360, which only hardened the `reference` field; deployments that applied that fix remain affected through the `callback` and `interval` fields.
Users of apache-airflow are recommended to upgrade to 3.4.0 or later. |
| Apache Airflow's scheduler fully deserializes XCom values written by task code while evaluating task dependencies. A Dag author, who controls what a task writes to XCom, therefore controls data that is deserialized inside the scheduler process - a context the Airflow security model reserves for code installed by the Deployment Manager, above the worker-scoped execution capability a Dag author is documented to have. Deployments that treat Dag authors as less trusted than Deployment Managers are affected, and the scheduler must be evaluating a task dependency that reads a task-written XCom value. Users of apache-airflow are recommended to upgrade to version 3.4.0 or later, which restricts dependency evaluation to primitive XCom values. |
| Apache Airflow did not reject reserved serialization keys inside a Dag run's `conf`. A user allowed to trigger a Dag that uses a deadline alert with an asynchronous callback could pass a `conf` that, once the deadline was missed, either crashed the scheduler repeatedly or was rebuilt into objects inside the Triggerer. Users are advised to upgrade to apache-airflow 3.4.0 or later. |
| Apache Airflow's asynchronous connection test checked permissions when the test was queued — only create permission when the connection ID did not exist yet — but, when the test completed with `commit_on_success`, wrote the tested connection under that ID. A user allowed to create but not edit connections could overwrite a connection someone else had created in the meantime. Only deployments that enable the non-default `[core] test_connection` setting are affected. Users are advised to upgrade to apache-airflow 3.4.0 or later. |
| Apache Airflow 2.4.0, and versions before 2.9.3, has a vulnerability that allows authenticated DAG authors to craft a doc_md parameter in a way that could execute arbitrary code in the scheduler context, which should be forbidden according to the Airflow Security model. Users should upgrade to version 2.9.3 or later which has removed the vulnerability. |
| Apache Airflow Amazon provider: the AWS auth manager's SAML login flow does not bind the authentication response to the browser that began it. The login handler discards the AuthnRequest ID and the callback validates the assertion without requiring a matching InResponseTo, so an unauthenticated attacker who can cause a victim to load a page can complete a SAML login in the victim's browser using the attacker's own assertion, silently logging the victim into the attacker's Airflow account. Subsequent work the victim performs lands in a session the attacker controls.
Affects deployments using the AWS auth manager with SAML authentication. The victim needs only to visit an attacker-controlled page; no Airflow account or credential is required of the attacker. This is the same login-CSRF class fixed in the Keycloak auth manager as CVE-2026-40948.
Users of apache-airflow-providers-amazon are recommended to upgrade to version 9.38.0, which fixes the issue. |
| In apache-airflow-providers-ssh before 7.0.1, SSHRemoteJobOperator quoted the values of its templated `environment` parameter only once, although they are placed inside an already-quoted wrapper script, so shell syntax such as `$(...)` in a value was executed on the remote SSH host. In a Dag that passes trigger-time input such as `params` or `dag_run.conf` into `environment`, a user who can trigger that Dag but cannot author Dags could run arbitrary commands on the remote host as the SSH connection's user. Users are advised to upgrade apache-airflow-providers-ssh to 7.0.1 or later. |
