CVE-2026-31987

Published Apr 16, 2026

Last updated 6 months ago

CVSS high 7.5
Jwt

Overview

Description
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.
Source
security@apache.org
NVD status
Analyzed
Products
airflow

Risk scores

CVSS 3.1

Type
Secondary
Base score
7.5
Impact score
3.6
Exploitability score
3.9
Vector string
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
Severity
HIGH

Weaknesses

security@apache.org
CWE-532

Social media

Hype score
Not currently trending

Configurations

Related CVEs

  1. PyJWT is a Python implementation of JSON Web Token standards. Prior to 2.14.0, is_pem_format in jwt/utils.py is affected because is_pem_format does not recognize every PEM representation accepted by the cryptography loader. This occurs when an application mixes HMAC and asymmetric algorithms and supplies a mutated public-key PEM as raw key bytes. As a result, HMACAlgorithm.prepare_key treats the unrecognized asymmetric public key as an HMAC secret. Consequently, an attacker who knows the public key can forge authenticated HMAC tokens. This issue is fixed in version 2.14.0.•CVE-2026-102268
  2. PyJWT is a Python implementation of JSON Web Token standards. From 2.13.0 until 2.14.0, PyJWS._load in jwt/api_jws.py is affected because parser catches ValueError but not RecursionError. This occurs when a deeply nested token header reaches json.loads. As a result, RecursionError escapes the documented PyJWT error hierarchy. Consequently, an unauthenticated malformed token can cause a request-level failure and HTTP 500. This issue is fixed in version 2.14.0.•CVE-2026-102265
  3. 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.•CVE-2026-82355
  4. 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.•CVE-2026-86473
  5. 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.•CVE-2026-75158

References

Sources include official advisories and independent security research.