Apache Airflow CVEs.

In Apache Airflow versions before 3.1.6, and 2.11.1 the proxies and proxy fields within a Connection may include proxy URLs containing embedded authentication information. These fields were not treated as sensitive by default and therefore were not automatically masked in log output. As a result, when such connections are rendered or printed to logs, proxy credentials embedded in these fields could be exposed. Users are recommended to upgrade to 3.1.6 or later for Airflow 3, and 2.11.1 or later for Airflow 2 which fixes this issue

Disclosure Device Apache Airflow

A bug in `BaseSerialization.deserialize()` allowed unrestricted `import_string()` of attacker-controlled class paths when the Scheduler / API Server loaded a serialized DAG: a DAG author could embed a malicious trigger into a DAG to gain remote code execution on the API Server / Scheduler process, crossing the Airflow security boundary that DAG-author code must never execute in those processes. Users are advised to upgrade to `apache-airflow` 3.3.0 or later. As a defense-in-depth mitigation, deployments where DAG-author trust is limited can restrict the `[core] allowed_deserialization_classes` config to a narrow allowlist.

Code execution Server Apache Airflow

DAG Author (who already has quite a lot of permissions) could manipulate database of Airflow 2 in the way to execute arbitrary code in the web-server context, which they should normally not be able to do, leading to potentially remote code execution in the context of web-server (server-side) as a result of a user viewing historical task information. The functionality responsible for that (log template history) has been disabled by default in 2.11.1 and users should upgrade to Airflow 3 if they want to continue to use log template history. They can also manually modify historical log file names if they want to see historical logs that were generated before the last log template change.

Injection Server Apache Airflow

Apache Airflow 3 introduced a change to the handling of sensitive information in Connections. The intent was to restrict access to sensitive connection fields to Connection Editing Users, effectively applying a "write-only" model for sensitive values. In Airflow 3.0.3, this model was unintentionally violated: sensitive connection information could be viewed by users with READ permissions through both the API and the UI. This behavior also bypassed the `AIRFLOW__CORE__HIDE_SENSITIVE_VAR_CONN_FIELDS` configuration option. This issue does not affect Airflow 2.x, where exposing sensitive information to connection editors was the intended and documented behavior. Users of Airflow 3.0.3 are advised to upgrade Airflow to >=3.0.4.

Other Server Apache Airflow

When a DAG failed during parsing, Airflow’s error-reporting in the UI could include the full kwargs passed to the operators. If those kwargs contained sensitive values (such as secrets), they might be exposed in the UI tracebacks to authenticated users who had permission to view that DAG.  The issue has been fixed in Airflow 3.1.4 and 2.11.1, and users are strongly advised to upgrade to prevent potential disclosure of sensitive information.

Disclosure Web app Apache Airflow

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.

Code execution Server Apache Airflow

Apache Airflow 3.3.0 moved human-in-the-loop tasks from the triggerer to a new `awaiting_input` task state swept by the scheduler. That sweep deserializes the task instance's `next_kwargs` without an allow-list, so a Dag author — who controls that value through the task execution API — can cause an arbitrary module import and object instantiation inside the scheduler process, or terminate the scheduler job. No non-default configuration is required: the sweep runs unconditionally every 15 seconds, and the default `allowed_deserialization_classes` setting does not cover this code path. Versions before 3.3.0 are not affected, because human-in-the-loop tasks deferred onto the triggerer instead. This is a different code path from CVE-2026-58076, which covers the same unguarded exception-node deserialization reached elsewhere — deployments that applied that fix must upgrade for this issue as well. Users are advised to upgrade to apache-airflow 3.3.1 or later.

Code execution Library Apache Airflow

Apache Airflow versions 3.0.0 - 3.1.7, has vulnerability that allows authenticated UI users with permission to one or more specific Dags to view import errors generated by other Dags they did not have access to. Users are advised to upgrade to 3.1.7 or later, which resolves this issue

Disclosure Server Apache Airflow

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.

Injection Server Apache Airflow

Apache Airflow: the Core API logout endpoint revokes only a session token presented as the _token cookie. When a client logs out presenting its credential as an Authorization bearer header instead, the endpoint returns its normal logout response but revokes nothing, so the token remains valid until it expires. An attacker who already holds a copy of that token keeps the victim's access after the victim has logged out and believes the session ended; the default token lifetime is 24 hours and is configurable. Affects API clients that authenticate with a bearer token rather than the browser session cookie. The attacker must already possess a copy of a valid token; obtaining one is outside the scope of this issue, and no privileges beyond the victim's own are gained. Users of apache-airflow are recommended to upgrade to apache-airflow version 3.3.2 or later, which fixes the issue.

Other Browser & mail Apache Airflow

JWT Tokens used by tasks were exposed in logs. This could allow UI users to act as Dag Authors. Users are advised to upgrade to Airflow version that contains fix. Users are recommended to upgrade to version 3.2.0, which fixes this issue.

Disclosure Server Apache Airflow

When a request to the Airflow core API carries both a session cookie and an explicit `Authorization: Bearer` token, Airflow resolves the caller from the cookie and ignores the bearer token, inverting the intended precedence of bearer over cookie. The request then executes -- and is recorded in the audit log -- as the cookie's principal rather than the identity the client explicitly presented. Only Apache Airflow 3.3.0 and 3.3.1 are affected. Earlier releases do not contain the code path that caches the cookie-derived user, and are not vulnerable. Exploiting this requires an attacker to first place a valid session cookie of their own into the victim's browser or client: for example by cookie tossing from a sibling subdomain, through cross-site scripting in a separate application sharing a parent domain, or via a shared workstation. Deployments that host the Airflow UI on a domain shared with other applications are therefore the most exposed; a deployment on a dedicated domain with no co-hosted applications is not reachable this way. The consequence is principal confusion and misattributed audit records rather than a direct privilege escalation. Users of 3.3.0 or 3.3.1 should upgrade to Apache Airflow 3.3.2 or later, which resolves the caller from the explicitly supplied credential whenever one is present.

XSS Browser & mail Apache Airflow

Apache Airflow versions 3.1.0 through 3.1.7 session token (_token) in cookies is set to path=/ regardless of the configured [webserver] base_url or [api] base_url. This allows any application co-hosted under the same domain to capture valid Airflow session tokens from HTTP request headers, allowing full session takeover without attacking Airflow itself. Users are recommended to upgrade to Apache Airflow 3.1.8 or later, which resolves this issue.

Other Server Apache Airflow

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.

Other Library Apache Airflow

Apache Airflow versions 3.0.0 through 3.1.8 DagRun wait endpoint returns XCom result values even to users who only have DAG Run read permissions, such as the Viewer role.This behavior conflicts with the FAB RBAC model, which treats XCom as a separate protected resource, and with the security model documentation that defines the Viewer role as read-only. Airflow uses the FAB Auth Manager to manage access control on a per-resource basis. The Viewer role is intended to be read-only by default, and the security model documentation defines Viewer users as those who can inspect DAGs without accessing sensitive execution results. Users are recommended to upgrade to Apache Airflow 3.2.0 which resolves this issue.

Other Server Apache Airflow

Apache Airflow's scheduler-side deadline-reference decoder (`SerializedCustomReference.deserialize_reference`) imported and dispatched arbitrary class paths drawn from DAG-author-controlled serialized state without an allowlist or plugin-registry gate. A DAG author whose code reaches the scheduler — the default on single-host deployments where the DAG bundle is importable from the scheduler process — could embed a custom `DeadlineReference` whose serialized form named an attacker-controlled module path, causing the scheduler to `import_string(...)` and instantiate that class with a live SQLAlchemy session attached. Affects deployments where DAG-author code is less trusted than the scheduler process. Users are advised to upgrade to `apache-airflow` 3.2.2 or later.

Code execution Web app Apache Airflow

When user logged out, the JWT token the user had authtenticated with was not invalidated, which could lead to reuse of that token in case it was intercepted. In Airflow 3.2 we implemented the mechanism that implements token invalidation at logout. Users who are concerned about the logout scenario and possibility of intercepting the tokens, should upgrade to Airflow 3.2+ Users are recommended to upgrade to version 3.2.0, which fixes this issue.

Other Server Apache Airflow

The Bulk Variables API in Apache Airflow called the redactor without passing the variable's key, so the key-based `should_hide_value_for_key` check (which triggers on secret-suffixed key names like `*_password` / `*_token` / `*_secret`) could not fire for JSON-decodable variable values. An authenticated UI/API user with bulk Variable read permission could retrieve plaintext values from JSON variables whose key would otherwise trigger redaction. Affects deployments that store sensitive values in JSON-typed Airflow Variables under secret-suffixed key names. Users are advised to upgrade to `apache-airflow` 3.3.0 or later (the fix landed on `main` after 3.2.2; no 3.2.x backport).

Disclosure Web app Apache Airflow

The Config API in Apache Airflow surfaced per-key secrets-backend overrides (environment variables like `AIRFLOW__SECRETS__BACKEND_KWARG__SECRET_ID` and `AIRFLOW__WORKERS__SECRETS_BACKEND_KWARG__SECRET_ID`) as synthetic config options whose option names were not in `sensitive_config_values`, so the masker did not redact them. An authenticated UI/API user with Config read permission could retrieve plaintext secrets-backend credentials (Vault `role_id` / `secret_id`, etc.) from the Config API output. Affects deployments that configure secrets backends via per-key environment overrides. Users are advised to upgrade to `apache-airflow` 3.3.0 or later.

Disclosure Web app Apache Airflow

In Apache Airflow before 3.3.0, the REST API task-instance detail and list endpoints returned a deferred task's trigger kwargs without masking. When a deferred operator passed a secret (for example a provider API key) into its trigger, any authenticated user with DAG-scoped task-instance read access for that DAG could read that secret in clear text while the task was deferred. Users should upgrade to apache-airflow 3.3.0 or later, which masks sensitive values in trigger kwargs returned by the API.

Disclosure Server Apache Airflow

A bug in the login redirect route in Apache Airflow allowed authenticated users to craft URLs that bypassed the `is_safe_url` check, enabling redirection from a trusted Airflow domain to an attacker-controlled origin. Users are advised to upgrade to `apache-airflow` 3.2.2 or later. As a defense-in-depth mitigation, deployment operators can place Airflow behind a reverse proxy that strips off-domain `next=` query parameters before they reach the login endpoint.

Other Server Apache Airflow

Apache Airflow's `/assets/events` API returned asset events for every Dag in the deployment, with no filter restricting them to the Dags the caller is authorized to read. Any authenticated user holding asset-read access could therefore enumerate asset events — including the source Dag ID, task ID, run ID and event timestamps — for Dags they have no permission to see. Because the filter was also absent from the count query, `total_entries` and pagination disclosed the existence of hidden Dags even without inspecting individual rows. Deployments are affected whenever per-Dag access control is used to separate teams or tenants; no special configuration is required. Upgrade to apache-airflow 3.3.2 or later.

Disclosure Server Apache Airflow

A bug in Apache Airflow's `/ui/dependencies` scheduling graph endpoint applied the caller's readable-Dag filter to the top-level serialized Dag key but still emitted referenced Dag IDs through the `dep.source` and `dep.target` fields of trigger / sensor dependency entries. An authenticated UI user with read permission on some Dags could enumerate the identifiers of other Dags they were not authorized to read by inspecting the dependency graph for trigger / sensor references. Affects deployments that rely on per-Dag read scoping to keep Dag identifiers private across teams. This is a residual gap in the fix for CVE-2026-28563, which filtered the top-level Dag key but did not propagate the filter into the trigger / sensor dep-source / dep-target fields. Users who already upgraded for CVE-2026-28563 should additionally upgrade to `apache-airflow` 3.3.0 or later to cover the residual trigger / sensor dependency leak.

Disclosure Web app Apache Airflow

In Apache Airflow versions before 3.1.6, when rendered template fields in a Dag exceed [core] max_templated_field_length, sensitive values could be exposed in cleartext in the Rendered Templates UI. This occurred because serialization of those fields used a secrets masker instance that did not include user-registered mask_secret() patterns, so secrets were not reliably masked before truncation and display. Users are recommended to upgrade to 3.1.6 or later, which fixes this issue

Disclosure Web app Apache Airflow

Apache Airflow's Task SDK rebuilt a `Callback` object from serialized data by re-running its constructor, which imports the module named by the stored callback path. Because `SyncCallback` is itself an Airflow class it passes the default `allowed_deserialization_classes` allow-list, so tightening that setting does not help. A Dag author — who controls a task instance's `next_kwargs` through the task execution API — can therefore cause an arbitrary module to be imported inside the scheduler process, when the scheduler's `awaiting_input` timeout sweep deserializes that value. No non-default configuration is required; the sweep runs unconditionally. Versions before 3.3.0 are not affected: the class existed, but the scheduler sweep that reaches it did not. This is a separate code path from CVE-2026-58076 and CVE-2026-67260, which cover different gadgets reaching deserialization — applying either of those fixes does not address this one. Users are advised to upgrade to apache-airflow 3.3.1 or later.

Code execution Library Apache Airflow

Before apache-airflow 3.3.0, a user authorized to read one Dag could disclose the source of other Dags co-located in the same source file. `GET /api/v2/dagSources/{dag_id}` — and the equivalent Dag-source view in the UI — returned the entire source file without redacting Dags the caller was not authorized to read, bypassing per-DAG read authorization. Deployments that co-locate multiple Dags in a single file and rely on per-DAG access control to limit source visibility are affected; single-Dag-per-file deployments are not. Upgrade to apache-airflow 3.3.0 or later.

Auth & access Web app Apache Airflow

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 resolves this issue.

Code execution Server Apache Airflow

The example example_xcom that was included in airflow documentation implemented unsafe pattern of reading value from xcom in the way that could be exploited to allow UI user who had access to modify XComs to perform arbitrary execution of code on the worker. Since the UI users are already highly trusted, this is a Low severity vulnerability. It does not affect Airflow release - example_dags are not supposed to be enabled in production environment, however users following the example could replicate the bad pattern. Documentation of Airflow 3.2.0 contains version of the example with improved resiliance for that case. Users who followed that pattern are advised to adjust their implementations accordingly.

Injection Web app Apache Airflow

A bug in Apache Airflow's XCom PATCH endpoint `PATCH /api/v2/xcomEntries/{key}` allowed an authenticated UI/API user with XCom write permission on a Dag to set XCom entries under reserved key names (e.g. `return_value`) that the matching POST endpoint already validated against `FORBIDDEN_XCOM_KEYS`. The endpoint also accepted serialized payload shapes the triggerer's deserializer treats as code; combined, this allowed RCE on the triggerer when the affected task next deferred. Affects deployments where untrusted users have XCom write permission on Dags that defer to the triggerer. This is a fix-bypass of CVE-2026-33858: PR #64148 added the `FORBIDDEN_XCOM_KEYS` validator only on the POST/set path; the PATCH path was not covered. Users who already upgraded for CVE-2026-33858 should additionally upgrade to `apache-airflow` 3.2.2 or later to cover the PATCH-path bypass.

Code execution Server Apache Airflow

Apache Airflow versions 3.1.0 through 3.1.7 missing authorization vulnerability in the Execution API's Human-in-the-Loop (HITL) endpoints that allows any authenticated task instance to read, approve, or reject HITL workflows belonging to any other task instance. Users are recommended to upgrade to Apache Airflow 3.1.8 or later, which resolves this issue.

Auth & access Server Apache Airflow

The `access_key` and `connection_string` connection properties were not marked as sensitive names in secrets masker. This means that user with read permission could see the values in Connection UI, as well as when Connection was accidentaly logged to logs, those values could be seen in the logs. Azure Service Bus used those properties to store sensitive values. Possibly other providers could be also affected if they used the same fields to store sensitive data. If you used Azure Service Bus connection with those values set or if you have other connections with those values storing sensitve values, you should upgrade Airflow to 3.1.8

Disclosure Server Apache Airflow

Apache Airflow's XCom `GET /api/v2/{...}/xcomEntries/{key}?deserialize=true` endpoint passed a string-literal payload through `BaseXCom.deserialize_value` without the `_check_forbidden_xcom_keys` guard, allowing an authenticated API user with XCom write-and-read access to instantiate arbitrary `airflow.*` classes on the API server (CWE-502). An authenticated user who can write an XCom value and then read it back with `deserialize=true` triggers the unsafe instantiation. Users are advised to upgrade to apache-airflow 3.3.1 or later, which rejects reserved XCom serialization keys submitted as JSON string literals.

Code execution Server Apache Airflow

API users via `/api/v2/dagReports` could perform Dag code execution in the context of the api-server if the api-server was deployed in the environment where Dag files were available.

Other Server Apache Airflow

An example dag `example_dag_decorator` had non-validated parameter that allowed the UI user to redirect the example to a malicious server and execute code on worker. This however required that the example dags are enabled in production (not default) or the example dag code copied to build your own similar dag. If you used the `example_dag_decorator` please review it and apply the changes implemented in Airflow 3.0.5 accordingly.

Injection Server Apache Airflow

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.

Disclosure Server Apache Airflow

Apache Airflow's serialization layer reconstructed exception nodes by calling `import_string()` on a class name taken from the serialized blob and instantiating it with arguments from the same blob, with no restriction on what could be imported. An operator's `executor_config` reaches that branch, so a Dag author could place a value there that causes an arbitrary callable to be imported and invoked -- for example `subprocess.check_output`, or `builtins.eval` on the `builtins`-prefixed variant. The code runs in the **Scheduler**, which reconstructs serialized Dags in its normal loop with no request involved, and in the **API server**, on any authenticated read of the Dag such as `GET /api/v2/dags/{dag_id}/details`. Both are components the Airflow security model states must never execute Dag-author code, and both hold the metadata database credentials and the JWT signing secret. No non-default configuration is required. This is a **different sink from CVE-2026-33264**, which covered only the trigger branch of the same deserializer: deployments that upgraded in response to that advisory are still affected through the exception branch and must upgrade again. Users are advised to upgrade to apache-airflow 3.3.1 or later, which restricts the imported class to a subclass of `BaseException`.

Code execution Server Apache Airflow

A vulnerability in Apache Airflow allowed authenticated UI users to view secret values in rendered templates due to secrets not being properly redacted, potentially exposing secrets to users without the appropriate authorization. Users are recommended to upgrade to version 3.1.4, which fixes this issue.

Other Web app Apache Airflow

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.

Other Server Apache Airflow

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.

Auth & access Server Apache Airflow

Apache Airflow versions 3.1.0 through 3.1.7 /ui/dependencies endpoint returns the full DAG dependency graph without filtering by authorized DAG IDs. This allows an authenticated user with only DAG Dependencies permission to enumerate DAGs they are not authorized to view. Users are recommended to upgrade to Apache Airflow 3.1.8 or later, which resolves this issue.

Other Server Apache Airflow

Apache Airflow versions 3.1.0 through 3.1.6 contain an authorization flaw that can allow an authenticated user with custom permissions limited to task access to view task logs without having task log access. Users are recommended to upgrade to Apache Airflow 3.1.7 or later, which resolves this issue.

Other Server Apache Airflow

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.

Other Server Apache Airflow

Before Airflow 3.2.0, it was unclear that secure Airflow deployments require the Deployment Manager to take appropriate actions and pay attention to security details and security model of Airflow. Some assumptions the Deployment Manager could make were not clear or explicit enough, even though Airflow's intentions and security model of Airflow did not suggest different assumptions. The overall security model [1], workload isolation [2], and JWT authentication details [3] are now described in more detail. Users concerned with role isolation and following the Airflow security model of Airflow are advised to upgrade to Airflow 3.2, where several security improvements have been implemented. They should also read and follow the relevant documents to make sure that their deployment is secure enough. It also clarifies that the Deployment Manager is ultimately responsible for securing your Airflow deployment. This had also been communicated via Airflow 3.2.0 Blog announcement [4]. [1] Security Model: https://airflow.apache.org/docs/apache-airflow/stable/security/jwt_token_authentication.html [2] Workload isolation: https://airflow.apache.org/docs/apache-airflow/stable/security/workload.html [3] JWT Token authentication: https://airflow.apache.org/docs/apache-airflow/stable/security/jwt_token_authentication.html [4] Airflow 3.2.0 Blog announcement: https://airflow.apache.org/blog/airflow-3.2.0/ Users are recommended to upgrade to version 3.2.0, which fixes this issue.

Disclosure Server Apache Airflow

User with CREATE and no UPDATE privilege for Pools, Connections, Variables could update existing records via bulk create API with overwrite action.

Other Server Apache Airflow

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.

Auth & access Server Apache Airflow

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.

Disclosure Server Apache Airflow

Apache Airflow's secrets masker hides values stored under sensitive key names when they are displayed in the UI. The masker's recursion-depth limit did not descend into values nested inside a list, tuple, or set beyond that limit, so an Airflow Variable holding such a deeply-nested value was shown unmasked in the Variables UI. The exposure is limited to the UI: any authenticated user who can see the Variable in the UI can already read its full value through the Variables REST API, so this does not disclose data the user could not otherwise obtain — the masking is a shoulder-surfing defense for the UI, not an access-control boundary. This is an incomplete-fix follow-up to CVE-2026-42358, whose fix made only the dictionary walk unbounded; lists, tuples, and sets beyond the depth limit remained unmasked in the UI. Deployments that applied the CVE-2026-42358 fix should also upgrade to address this residual case. Upgrade to apache-airflow 3.3.1 or later.

Disclosure Server Apache Airflow

Apache Airflow versions 3.0.0 through 3.1.7 FastAPI DagVersion listing API does not apply per-DAG authorization filtering when the request is made with dag_id set to "~" (wildcard for all DAGs). As a result, version metadata of DAGs that the requester is not authorized to access is returned. Users are recommended to upgrade to Apache Airflow 3.1.8 or later, which resolves this issue.

Other Server Apache Airflow

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

Other Server Apache Airflow

Airflow versions before 2.11.1 have a vulnerability that allows authenticated users with audit log access to see sensitive values in audit logs which they should not see. When sensitive connection parameters were set via airflow CLI, values of those variables appeared in the audit log and were stored unencrypted in the Airflow database. While this risk is limited to users with audit log access, it is recommended to upgrade to Airflow 2.11.1 or a later version, which addresses this issue. Users who previously used the CLI to set connections should manually delete entries with those connection sensitive values from the log table. This is similar but not the same issue as CVE-2024-50378

Disclosure Server Apache Airflow