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.

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/jwttokenauthentication.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/jwttokenauthentication.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.

The example examplexcom 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 - exampledags 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.

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.

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, totalentries 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.

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.

Apache Airflow's asset queued-events DELETE endpoints checked the caller's Dag-axis permission with READ instead of EDIT. Any authenticated user who could read a Dag could therefore delete that Dag's queued asset events, silently suppressing asset-triggered scheduling for it — a state-changing action gated on a read-only permission. Deployments are affected whenever asset-triggered scheduling is in use and Dag read access is granted more widely than Dag edit access, which is the normal RBAC arrangement; no special configuration is required. Upgrade to apache-airflow 3.3.2 or later.

Severity: low

Affected versions:

- Apache Airflow 3.0.0 before 3.3.2

Description:

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.

Credit:

OpenSec Intelligence (finder) Jarek Potiuk (remediation developer)

References:

https://github.com/apache/airflow/pull/72649 https://airflow.apache.org/ https://www.cve.org/CVERecord?id=CVE-2026-86473

Severity: low

Affected versions:

- Apache Airflow 3.3.0 before 3.3.2

Description:

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.

Credit:

Claude Security Scans (tool) Jarek Potiuk (remediation developer)

References:

https://github.com/apache/airflow/pull/72225 https://github.com/apache/airflow/pull/72723 https://airflow.apache.org/ https://www.cve.org/CVERecord?id=CVE-2026-82355

Severity: moderate

Affected versions:

- Apache Airflow before 3.3.2

Description:

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, totalentries 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.

Credit:

n0mi1k (finder) Jarek Potiuk (remediation developer)

References:

https://github.com/apache/airflow/pull/71741 https://airflow.apache.org/ https://www.cve.org/CVERecord?id=CVE-2026-75158

Apache Airflow Apache Kafka provider versions 1.15.0 before 2.0.0 resolve dotted-path strings found in a Kafka connection's extra field into Python callables via importstring, with no allowlist, and hand them to the confluent-kafka client which invokes them. Deployments that have enabled the Kafka event producer — dagruneventsenabled or taskinstanceeventsenabled, both disabled by default — build that client inside the scheduler process, so a user whose only privilege is editing Airflow connections gains arbitrary code execution in the control plane; the Airflow security model limits connection-configuration users to code execution on workers, not the scheduler. Deployments using Google Managed Kafka are not affected, because that code path overwrites any user-supplied oauthcb; plain brokers and Amazon MSK are exposed. Users are recommended to upgrade to apache-airflow-providers-apache-kafka 2.0.0 or later, which adds an allowlist configuration option for connection-string callbacks.

Apache Airflow FAB provider: deactivating a user account does not stop tokens issued to that account before deactivation. Password authentication correctly rejects the disabled account, but the Core API continues to accept an existing, unexpired token naming it, and lets that token mint a replacement — so the account keeps its role-scoped access indefinitely after an administrator has disabled it. The user replays their own legitimate credential; no signature forgery or privilege escalation is involved, and the access stays within the roles the account already held.

Affects deployments using Airflow 3 with the FAB auth manager and Core API token authentication, where an administrator deactivates an account whose row remains in the database and whose previously issued token has not expired. The trigger is administrative deactivation as a containment action, which silently fails to contain.

Users of apache-airflow-providers-fab are recommended to upgrade to version 3.9.0 or later, which rejects tokens naming a deactivated account.

Apache Airflow Keycloak provider: from Airflow 3.3 the Keycloak auth manager takes a user's identity from the signed Airflow session token but takes the Keycloak access and refresh tokens used for every authorization decision from separate, unauthenticated cookies, and never checks that the two describe the same subject. A user who holds any valid Airflow login of their own, together with another subject's Keycloak access or refresh token obtained out of band, can pair the two: Airflow then authorizes requests with the foreign token's privileges while the session identity, audit log and cache keys continue to name the attacker's own account. The refresh path re-issues an Airflow session token for the original identity carrying the foreign tokens, so the mismatched pairing survives across sessions.

Affects deployments running Airflow 3.3 or later with the Keycloak auth manager. Earlier versions carried the Keycloak tokens inside the signed session token, so the binding existed and was lost when they moved into separate cookies.

Users of apache-airflow-providers-keycloak are recommended to upgrade to version 0.10.0 or later, which binds the cookie-supplied tokens to the session identity.

Apache Airflow's environment-variable secrets backend resolved a team-scoped Connection or Variable from the wrong team's scope. The guard meant to prevent this only ran when no team scope was supplied, and its pattern could not match a team name containing an underscore, which team names are allowed to contain. When the guard did not apply, the lookup fell through to an unconditional global read that resolved the stored AIRFLOWCONN<TEAM><ID> variable regardless of which team asked. In multi-team mode an authenticated user of one team could therefore have POST /api/v2/connections/test resolve another team's Connection and authenticate outward with that team's credentials; the endpoint uses the credentials rather than returning them. Exploitation requires [core] multiteam enabled, [core] testconnection set to Enabled (it ships Disabled), team-scoped secrets provisioned as environment variables in the API-server process, and knowledge of the encoded identifier. Redirecting the test at an attacker-controlled host is separately blocked. Users are advised to upgrade to apache-airflow 3.3.1 or later.

Apache Airflow's asset materialization endpoint (POST /api/v2/assets/{assetid}/materialize) and the XCom result check on waitdagrununtilfinished authorized the target Dag without its team, unlike every other authorization site. A team-aware auth manager distinguishes a team-scoped Dag from a global one by that field -- the Keycloak auth manager, for example, checks the DAG resource instead of DAG:<team> -- so the team-scoped permission that should gate the request was never consulted. In a deployment running multi-team mode with a team-aware auth manager, an authenticated user in one team could trigger Dag runs belonging to another team, supplying their own dagrunid and conf, and could read another team's XCom values. Deployments using the FAB auth manager are unaffected, as it has no multi-team support. Users are advised to upgrade to apache-airflow 3.3.1 or later, which resolves the Dag's team at both sites.

Apache Airflow wrote Variable values and Connection extra contents to the audit log in cleartext when they were submitted through the bulk endpoints (PATCH /api/v2/variables and PATCH /api/v2/connections). The audit-log masking recognised only top-level request fields, and a bulk request nests its entities two levels below, so no masking was applied to them. Any authenticated user with audit-log read access -- who need not hold Variables or Connections read at all -- could recover those secrets verbatim, and the Connection extra copy is stored unencrypted in the log while the connection table encrypts it. The Airflow UI's Import Variables action posts to this endpoint, so an ordinary operator import wrote every secret in the file to the log. This is a different code path from CVE-2026-50204: that fix shipped in 3.3.0 and covers the single-entity endpoints only, so deployments that upgraded in response to that advisory remain affected and must upgrade again. Users are advised to upgrade to apache-airflow 3.3.1 or later.

Apache Airflow's Task SDK did not mask the contents of a Variable whose JSON value is a list, so secrets stored in that shape appeared in cleartext in task logs and in the Rendered Templates UI. Masking was applied only when the deserialized value was a string or a dict; a list at the top level matched neither and was returned unmasked. Any authenticated user able to read the logs or rendered templates of a task that references such a Variable could recover the values, with no special configuration required. This is the list-shaped counterpart of CVE-2026-59244, whose fix covered the dict case only, so deployments that upgraded in response to that advisory remain affected and must upgrade again. Users are advised to upgrade to apache-airflow 3.3.1 or later.

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 alloweddeserializationclasses allow-list, so tightening that setting does not help. A Dag author — who controls a task instance's nextkwargs through the task execution API — can therefore cause an arbitrary module to be imported inside the scheduler process, when the scheduler's awaitinginput 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.

Apache Airflow's Backfill API authorized a request against a Dag id supplied by the caller whenever the backfillid path segment failed to parse. The authorization dependency parsed it with int() while the route handler parsed it as pydantic's NonNegativeInt, which accepts values int() rejects (1.0 coerces to 1); FastAPI resolves dependencies before endpoint validation, so the two acted on different Dags. An authenticated user holding edit permission on any single Dag could therefore read, pause and cancel backfills belonging to any other Dag, including moving another Dag's queued runs to failed. No non-default configuration is required and backfill ids are sequential, so finding a target is trivial. Users are advised to upgrade to apache-airflow 3.3.1 or later, which parses the backfill id with the same type the routes declare.

Apache Airflow's Config API did not mask team-scoped sensitive configuration values in multi-team deployments. When an administrator has enabled multi-team mode and exposed the Config API, an authenticated Viewer holding only configuration-read access — with no prior access to the secret — could read a team-scoped Celery broker URL, including its embedded credentials, in cleartext, while the equivalent global option was correctly masked. The secrets masker matched only base section and option names and did not normalize team-prefixed sections before the sensitivity check (CWE-200). This is a distinct masker bypass from CVE-2026-48828 and CVE-2026-48892: deployments that upgraded to apache-airflow 3.3.0 to address those issues remain affected by this team-scoped variant. Users are advised to upgrade to apache-airflow 3.3.1 or later, which normalizes team-scoped sections before masking.

Apache Airflow 3.3.0 moved human-in-the-loop tasks from the triggerer to a new awaitinginput task state swept by the scheduler. That sweep deserializes the task instance's nextkwargs 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 alloweddeserializationclasses 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.

Apache Airflow's secrets masker did not mask var.json Variable values whose value is a dict in the Rendered Templates UI — the dict value failed an isinstance(str) guard — so a secret stored as a JSON Variable and referenced in a template via var.json was displayed in cleartext to any user with access to that task's Rendered Templates view. Users are advised to upgrade to apache-airflow 3.3.1 or later, which masks nested Variable values regardless of type.

Apache Airflow's serialization layer reconstructed exception nodes by calling importstring() 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 executorconfig 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.checkoutput, 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/{dagid}/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.

Apache Airflow's XCom GET /api/v2/{...}/xcomEntries/{key}?deserialize=true endpoint passed a string-literal payload through BaseXCom.deserializevalue without the checkforbiddenxcomkeys 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.

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.

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.

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.

The Config API in Apache Airflow surfaced per-key secrets-backend overrides (environment variables like AIRFLOWSECRETSBACKENDKWARGSECRETID and AIRFLOWWORKERSSECRETSBACKENDKWARGSECRETID) as synthetic config options whose option names were not in sensitiveconfigvalues, so the masker did not redact them. An authenticated UI/API user with Config read permission could retrieve plaintext secrets-backend credentials (Vault roleid / secretid, 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.

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/{dagid} — 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.

The Bulk Variables API in Apache Airflow called the redactor without passing the variable's key, so the key-based shouldhidevalueforkey 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).