| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| Apache Airflow's Teradata provider embedded cloud storage credentials directly into SQL statements. `S3ToTeradataOperator` and `AzureBlobStorageToTeradataOperator` interpolate the source bucket's credentials as plain string literals into the `CREATE MULTISET TABLE ... LOCATION` statement whenever the bucket is private and no `teradata_authorization_name` is configured — which is the default credential path for both operators. The statement is then logged and executed, so the credentials reach two places outside the operator's control.
The two operators expose different credentials through different channels, and deployments should check both. `S3ToTeradataOperator` takes its values from `s3_hook.get_credentials()`, which under an instance profile or IRSA returns runtime AWS credentials that were never registered with Airflow's secrets masker — and the STS session token is runtime-generated and therefore unmasked even when an AWS connection is configured. Those credentials appear **in the Airflow task log**, readable by any user with log-view permission on the Dag. `AzureBlobStorageToTeradataOperator` takes its storage account key from the connection, so the masker usually redacts the task-log copy; its exposure is the Teradata side. **Both** operators write the credentials into Teradata's DBQL query logs and live monitoring views, where Airflow's masking never applies and the values persist for that system's log retention period.
Affects deployments using either operator against a private bucket or container without a Teradata `AUTHORIZATION` object. Users are advised to upgrade to `apache-airflow-providers-teradata` `3.7.0` or later, which keeps the credential-bearing statement out of the Airflow task log. Upgrading does not remove the credentials from Teradata's query logs and monitoring views, which Airflow cannot redact: users should configure `teradata_authorization_name` with a Teradata `AUTHORIZATION` object so that credentials are never inlined, and should rotate any credentials previously used through the inline path. |
| Apache Airflow's Snowflake provider did not validate the connection's `account` and `region` fields before interpolating them into request URLs. The SQL API endpoint is built as `https://{account}.snowflakecomputing.com/api/v2/statements`, so an `account` value containing `/`, `?` or `#` demotes the intended domain to a path, query or fragment and leaves the attacker in control of the request host.
The provider sends that request with an `Authorization: Bearer` header carrying a JWT minted from the connection's private key, or the configured OAuth or programmatic access token. A user who can edit the Snowflake connection but cannot read its secrets — Airflow gives connection-configuration users write-only access to stored credentials, and a `private_key_file` lives on the worker rather than in the connection — can therefore cause a valid token for the account to be delivered to a host of their choosing and replay it against the genuine Snowflake endpoint. No Dag-authoring ability is required: the attacker edits the connection and waits for an existing Dag to use it. The same unvalidated value was also used to build the OAuth token-request URL and the Cortex Agent base URL.
Affects deployments where Snowflake connections are editable by users who are not trusted with the connection's credentials. Users are advised to upgrade to `apache-airflow-providers-snowflake` `6.18.0` or later, which rejects `account` and `region` values containing anything other than letters, digits, `.`, `_` and `-` in every URL the provider builds from them. |
| The Apache Airflow Teradata provider's compute-cluster example Dag declared every one of its Dag Params as unconstrained free text and templated them straight into the compute-cluster operators, which interpolate those values into Teradata DDL. A user who is permitted to trigger that Dag - a lower-trust role than the Dag author, and one that needs no Teradata credentials of its own - could therefore supply SQL fragments that execute under the connection the task runs as, and could additionally redirect the task at any other connection defined in the deployment, because the connection id was itself a free-text Param. Only deployments that run this example Dag, or a Dag copied from it, are affected; the provider's operator code is unchanged. Users of apache-airflow-providers-teradata are recommended to upgrade to version 3.7.0 or later, whose example constrains the Params to validated identifiers and a closed value set and removes connection selection and free-form option strings from trigger-time input. Upgrading does not change a Dag already copied from the example; users who copied it should apply the same constraints to their copy. |
| Apache Airflow's Google provider built Google Drive search expressions by interpolating file and folder names directly into single-quoted string literals, without escaping the quote character that delimits them. A name containing an apostrophe therefore terminated the literal early and appended clauses of the attacker's choosing to the query.
The names are frequently not written by the Dag author. In a wildcard `gcs_to_gdrive` transfer they come from the source bucket listing, so anyone able to create objects in that bucket controls them — typically an external data producer or an ingest-only service account, a different trust principal from the Dag author. An injected clause can broaden the match and so steer which file or folder the hook resolves: an upload can be directed into a folder the attacker named, and, because downloads select the most recently modified match, a download can return a file they placed rather than the one the Dag asked for.
Affects deployments passing externally-sourced names to the Google Drive hook, including wildcard `gcs_to_gdrive` transfers from buckets writable by less-trusted principals. Users are advised to upgrade to `apache-airflow-providers-google` `22.6.0` or later, which escapes quote and backslash characters in every value interpolated into a Drive query. |
| Apache Airflow HashiCorp provider: the HashiCorp Vault secrets backend's team-scope guard can be bypassed with a user-controlled key. In a multi-team deployment, a Dag author scoped to one team can supply a Variable key containing a path separator that causes the backend to resolve a secret belonging to a different team, because after the team-scoped lookup misses the backend falls back to a team-agnostic path concatenated from the unvalidated key. The Execution API Variables route accepts a path-shaped key, so this is reachable from ordinary Dag code.
Affects multi-team deployments using the HashiCorp Vault secrets backend. Single-team deployments are not affected, as there is no cross-team boundary to cross. This is the same class as CVE-2026-86465, CVE-2026-68870, CVE-2026-68871 and CVE-2026-68872 in the Akeyless, Azure Key Vault, Yandex Lockbox and Amazon secrets backends.
Users of apache-airflow-providers-hashicorp are recommended to upgrade to version 4.8.0 or later, which fixes the issue. |
| 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, `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. |
| 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. |
| Apache Airflow Akeyless provider: the Akeyless secrets backend's team-scope guard can be bypassed with a user-controlled key. In a multi-team deployment, a Dag author scoped to one team can supply a Variable key containing a path separator that causes the backend to resolve a secret belonging to a different team, because the lookup path is concatenated from an unvalidated key after the team-scoped lookup misses. The Execution API Variables route accepts a path-shaped key, so this is reachable from ordinary Dag code.
Affects multi-team deployments using the Akeyless secrets backend. Single-team deployments are not affected, as there is no cross-team boundary to cross. This is the same class as CVE-2026-68870, CVE-2026-68871 and CVE-2026-68872 in the Azure Key Vault, Yandex Lockbox and Amazon secrets backends.
Users of apache-airflow-providers-akeyless are recommended to upgrade to version 0.3.1 or later, which fixes the issue. |
| 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 `import_string`, with no allowlist, and hand them to the confluent-kafka client which invokes them. Deployments that have enabled the Kafka event producer — `dag_run_events_enabled` or `task_instance_events_enabled`, 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 `oauth_cb`; 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: the Authentik OAuth path in the FAB auth manager does not validate the issuer or audience claims of the id_token it accepts. An attacker holding a token that the same Authentik identity provider minted for a different client application can present it to Airflow and be authenticated as the user it names, because the audience claim is never checked. Affects deployments using the FAB auth manager with Authentik OAuth where the same Authentik instance also serves other applications; the attacker needs a valid token for any of those other applications, not for Airflow.
CVE-2026-75156 corrected the same missing validation on the Azure AD path in this file; the Authentik path was left unchanged and is fixed here. Deployments that applied the CVE-2026-75156 fix and use Authentik must also upgrade for this one.
Users of apache-airflow-providers-fab are recommended to upgrade to version 3.9.0 or later, which fixes the issue. |
| Apache Airflow FAB provider: changing a user's password through the Admin user-edit PATCH endpoint does not invalidate that user's existing database-backed sessions. An attacker who already holds a copy of the victim's session cookie keeps full access as that user after the password change, so the password reset does not evict them. Affects deployments using the FAB auth manager with database-backed sessions; an administrator (or the user themselves) performing a routine password change is the trigger, and no attacker interaction with the endpoint is needed.
This is a second, independent route to the outcome addressed by CVE-2026-82311, which corrected an identifier comparison in the session-invalidation helper. That fix does not repair this endpoint, because the PATCH path never calls the helper at all. Deployments that applied the CVE-2026-82311 fix must also upgrade for this one.
Users of apache-airflow-providers-fab are recommended to upgrade to version 3.9.0 or later, which fixes the issue. |
| Apache Airflow FAB provider: resetting a user's password does not delete that user's existing database-backed sessions, despite documented behaviour that it does. The cleanup compares the string identifier Flask-Login stores in the session against the user's integer database identifier, so the comparison never matches and no session is removed. An attacker who already holds a copy of the victim's session cookie keeps access as that user after the password change, so the reset does not evict them.
Affects deployments using the FAB auth manager with `[fab] session_backend=database`. The trigger is an administrator (or the user) running the supported password-reset command as a containment action after a session cookie has been compromised; the secure-cookie backend is out of scope, as it documents that it cannot centrally delete sessions.
apache-airflow-providers-fab 3.9.0 also fixes CVE-2026-86462, a second, independent route to the same outcome via the Admin user-edit endpoint; a single upgrade closes both.
Users of apache-airflow-providers-fab are recommended to upgrade to version 3.9.0 or later, which compares the identifiers consistently. |
| 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: the unauthenticated token endpoint accepts a client-credentials grant for any confidential client registered in the Keycloak realm, not only the client configured for Airflow. No allowlist restricts which client ids may authenticate, so the credentials of an unrelated application that happens to share the realm are valid Airflow login credentials, and Airflow mints a signed session token for that application's service account. The endpoint also answers unauthenticated credential guesses against Keycloak under Airflow's identity.
Affects deployments using the Keycloak auth manager whose realm is shared with other confidential clients. The attacker needs valid credentials for any one of those clients, not for Airflow. Resource authorization is still evaluated per subject, so the access gained is whatever that service account holds, plus any endpoint gated only on being authenticated.
Users of apache-airflow-providers-keycloak are recommended to upgrade to version 0.10.0 or later, which accepts only the configured client on that grant. |
| 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 FAB provider versions 3.7.3 through 3.8.0 do not validate the issuer or audience of Azure AD `id_token`s during OAuth login. Deployments are affected only when the FAB auth manager is configured with Azure AD as an OAuth provider. Because the signing keys are fetched from Microsoft's **multi-tenant** JWKS endpoint, an `id_token` minted in *any* Azure tenant — including one the attacker creates — passes signature verification, and the username and role assignments are then read from that attacker-controlled token. Anyone able to register an Azure tenant can therefore authenticate to the Airflow UI with no prior access to the deployment.
The fix for **CVE-2026-59243** was incomplete, and this advisory closes the remaining gap: that fix made the provider verify the `id_token` signature, but did not add issuer or audience checks. Operators who already applied the CVE-2026-59243 fix are **still affected and must upgrade again** — 3.7.3 is the release that shipped that fix, so every version containing it falls inside this affected range. Upgrade to apache-airflow-providers-fab `3.8.1` or later. |
| 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 `AIRFLOW_CONN__<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] multi_team` enabled, `[core] test_connection` 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 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. |
