| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| 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. |
| Apache Airflow providers-google's `ComputeEngineSSHHook` disables SSH host-key verification by default, exposing SSH traffic between an Airflow worker and a Compute Engine VM to in-path network attackers who can intercept or modify the session. Users are advised to upgrade to `apache-airflow-providers-google` 22.0.0 or later. |
| A bug in the GET `/api/v2/connections/{connection_id}` REST API endpoint in Apache Airflow allowed an authenticated UI/API user with Connection-read permission to retrieve secrets stored in a Connection's `extra` JSON blob under field names not present in the redaction allowlist (`DEFAULT_SENSITIVE_FIELDS`) — for example, official Slack-provider credential field names were returned in plaintext. Affects deployments that store credentials in Connection `extra` blobs and grant Connection-read access to multiple users. Users are advised to upgrade to `apache-airflow` 3.2.2 or later. As a defense-in-depth mitigation, deployment operators can store sensitive credential values in a secret-backend rather than inlined into the Connection's `extra` field. |
| The structure_data 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. |
| A bug in Apache Airflow's rendered-template field handling caused nested sensitive-key masking (e.g. nested `password` / `token` / `secret` / `api_key` keys inside a JSON template structure) to be bypassed when the rendered field exceeded `[core] max_templated_field_length`: Airflow stringified the structure before redaction, losing the nested key context, and persisted the plaintext value into `rendered_fields`. An authenticated UI/API user with permission to read rendered template fields could harvest secret values intended to be masked. Affects deployments where Dag authors pass structured JSON to operators with nested sensitive keys. This is a variant of `CWE-200` previously addressed for the user-registered `mask_secret()` patterns in CVE-2025-68438; that fix did not cover the nested sensitive-keyword allowlist. Users who already upgraded for CVE-2025-68438 should additionally upgrade to `apache-airflow` 3.2.2 or later to cover the nested-key path. |
| Apache Airflow FAB Auth Manager contains an LDAP filter injection vulnerability (CWE-90) that allows unauthenticated attackers to exfiltrate directory data or bypass authentication. Upgrade to apache-airflow-providers-fab 3.6.4 or later. If immediate upgrade is not possible, disable LDAP authentication until the provider can be updated. |
| In the AWS Secrets Manager and SSM Parameter Store secrets backends of `apache-airflow-providers-amazon` prior to 9.28.0, the team-scoping logic could resolve a `conn_id` containing a `/` (e.g. `"my_team/conn"`) to the same path as another team's team-scoped secret when the caller had no team context. A privileged caller without team context could therefore retrieve another team's secret by crafting a colliding `conn_id`. Fixed in 9.28.0 by switching the team-scope separator to `--` and rejecting team-shaped `conn_id`s when team context is absent. Affects the experimental multi-tenant teams feature only. Users are recommended to upgrade to `apache-airflow-providers-amazon` 9.28.0, which fixes the issue. |
| JWT tokens that were used by workers in Kubernetes Executors have been exposed to users who had read only access to Kuberentes Pods. This could allow users with just read-only access to perform actions that were only available to running tasks via Task SDK and potentially allow to modify state of Airflow Database for tasks. |
| The Elasticsearch logging provider, when configured with a `host` URL that embeds credentials (for example `https://user:password@server.example.com:9200`), wrote the full host URL — including the embedded credentials — into task logs. Any user with task-log read permission could harvest the backend credentials. Users are advised to upgrade to `apache-airflow-providers-elasticsearch` 6.5.3 or later and, as a defense-in-depth measure, configure the backend credentials via a secret backend rather than embedding them in the `[elasticsearch] host` URL. |
| The OpenSearch logging provider, when configured with a `host` URL that embeds credentials (for example `https://user:password@server.example.com:9200`), wrote the full host URL — including the embedded credentials — into task logs. Any user with task-log read permission could harvest the backend credentials. Users are advised to upgrade to `apache-airflow-providers-opensearch` 1.9.1 or later and, as a defense-in-depth measure, configure the backend credentials via a secret backend rather than embedding them in the `[opensearch] host` URL. |
| The Keycloak authentication manager in `apache-airflow-providers-keycloak` did not generate or validate the OAuth 2.0 `state` parameter on the login / login-callback flow, and did not use PKCE. An attacker with a Keycloak account in the same realm could deliver a crafted callback URL to a victim's browser and cause the victim to be logged into the attacker's Airflow session (login-CSRF / session fixation), where any credentials the victim subsequently stored in Airflow Connections would be harvestable by the attacker. Users are advised to upgrade `apache-airflow-providers-keycloak` to 0.7.0 or later. |
| Apache Airflow's SMTP provider `SmtpHook` called Python's `smtplib.SMTP.starttls()` without an SSL context, so no certificate validation was performed on the TLS upgrade. A man-in-the-middle between the Airflow worker and the SMTP server could present a self-signed certificate, complete the STARTTLS upgrade, and capture the SMTP credentials sent during the subsequent `login()` call. Users are advised to upgrade to the `apache-airflow-providers-smtp` version that contains the fix. |
| 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. |
| 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. |
| An example of BashOperator in Airflow documentation suggested a way of passing dag_run.conf in the way that could cause unsanitized user input to be used to escalate privileges of UI user to allow execute code on worker. Users should review if any of their own DAGs have adopted this incorrect advice. |
| In case of SQL errors, exception/stack trace of errors was exposed in API even if "api/expose_stack_traces" was set to false. That could lead to exposing additional information to potential attacker. Users are recommended to upgrade to Apache Airflow 3.2.0, which 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 |
| 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. |
