Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessIntercept valid JWT via network sniffing or XSS
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DeliveryWait for legitimate user logout
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ExploitReplay captured token in REST API requests
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ExecutionAccess Airflow workflows and credentials
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ImpactMaintain access until token expiration
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A07:2025 - Authentication Failures
ASVS 5.0
V7 - Session Management Session expiration enforcement
|
| Exploitation Conditions | Exploitation requires the attacker to first obtain a valid JWT token through interception, which depends on: deployment of Airflow over HTTP rather than HTTPS (enables passive network sniffing), access to the same network segment as authenticated users (for MITM or ARP spoofing attacks), presence of XSS vulnerabilities in Airflow or co-hosted applications (enables JavaScript-based token theft from browser storage), or physical/remote access to client devices where tokens are cached in browser memory or disk. The vulnerability itself does NOT create a token bypass - attackers MUST possess a legitimately issued token. Exploitation is LIMITED by: the JWT's built-in expiration time (default varies by Airflow configuration, typically 30-120 minutes), requirement for the user to have successfully authenticated before logout (cannot exploit tokens that were never issued), and network positioning to intercept tokens (purely remote attackers without network access cannot exploit without a separate token-stealing vulnerability). Organizations using HTTPS exclusively and network segmentation significantly reduce the attack surface, though insider threats or device compromise remain viable vectors. |
| Impact | The CVSS 9.1 (Critical) score reflects a theoretical worst-case scenario: network-accessible (AV:N), low complexity (AC:L), no authentication required (PR:N), no user interaction (UI:N), with high confidentiality and integrity impact. However, this rating is MISLEADING because exploitation requires the attacker to first INTERCEPT a valid JWT token - the vulnerability does NOT create tokens out of thin air. Real-world risk depends heavily on whether an attacker can obtain tokens via network sniffing (requires non-HTTPS deployment, rare in production), XSS attacks (separate vulnerability), or compromised client devices. The EPSS score of 0.01% (3rd percentile) and SSVC assessment (exploitation: none, automatable: yes, technical impact: partial) provide crucial context: despite the high CVSS, there is no evidence of active exploitation, and the attack requires a prerequisite step (token interception) not reflected in the CVSS vector's PR:N designation. The PR:N rating appears to assume the attacker already possesses the token, but obtaining that token IS a privilege requirement in practical terms. For organizations using HTTPS (industry standard), not exposing Airflow to untrusted networks, and without concurrent XSS vulnerabilities, real-world exploitability is significantly lower than the CVSS suggests. Organizations with Airflow exposed to public networks, using HTTP, or with shared client devices face elevated risk. CRITICAL DATA CONFLICT: CVSS PR:N contradicts the description's implicit requirement that attackers must first intercept valid tokens - verify whether 'no privileges required' assumes token possession or refers to a separate bypass vector. |
| Exploit ScenarioDerived | An attacker positions themselves on the same network as an Airflow administrator (via compromised WiFi, man-in-the-middle on corporate network, or malicious browser extension on a shared workstation) and captures the JWT token from an authenticated session through packet sniffing of HTTP traffic or extraction from browser local storage. After the administrator logs out of Airflow, believing the session is terminated, the attacker replays the captured JWT in API requests to Airflow's REST endpoints. The token remains valid until its expiration timestamp, allowing the attacker to trigger workflow DAGs, access sensitive connection credentials stored in Airflow, or modify pipeline configurations. No public proof-of-concept code identified, but token replay is a well-understood attack technique requiring only basic HTTP client tools like curl or Postman. |
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Alert meAnalysisAIv2 – Apr 17, 2026
Apache Airflow 3.0.0 through 3.1.x fails to invalidate JWT tokens at logout, allowing intercepted tokens to remain valid for unauthorized API access. This session management weakness enables replay attacks against the workflow orchestration platform's REST API. No active exploitation confirmed (EPSS 3rd percentile), but SSVC rates as automatable with partial technical impact. Vendor-released patch: Apache Airflow 3.2.0.
Earlier versions of this analysis (1)
JWT token reuse vulnerability in Apache Airflow 3.0.0 through 3.1.x allows unauthenticated remote attackers to impersonate authenticated users by intercepting and replaying tokens after legitimate logout. The framework failed to invalidate JWT authentication tokens during user logout operations, enabling session persistence beyond intended termination. Attackers with network access to intercept tokens can achieve unauthorized access to high-integrity operations. EPSS indicates low observed exploitation activity; no public exploit identified at time of analysis.
RemediationAI
Upgrade to Apache Airflow 3.2.0 or later, which implements JWT token invalidation at logout via changes in GitHub pull requests 56633 and 61339. Before patching, implement compensating controls: reduce JWT token expiration times to minimize the replay window (edit airflow.cfg webserver.access_token_expiration to 600 seconds or less, noting this requires users to re-authenticate more frequently), enforce HTTPS for all Airflow web interfaces to prevent passive token interception (configure webserver.web_server_ssl_cert and web_server_ssl_key), restrict network access to Airflow's webserver port (default 8080) to trusted IP ranges via firewall rules (reduces token exposure surface but does not prevent replay attacks from allowed networks), and implement short-lived refresh tokens if customizing authentication (requires code changes and operational complexity). Monitor for anomalous API access patterns such as simultaneous sessions from different IP addresses or access after logout events in webserver logs. Note that reducing token expiration creates operational friction for legitimate users who must authenticate more frequently. No workaround fully mitigates the issue; upgrade to 3.2.0 is the only complete fix. Advisory: https://lists.apache.org/thread/ovn8mpd8zkc604hojt7x3wsw3kc60x98.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in pypi
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Technical ContextAI · show details
Apache Airflow is a workflow orchestration platform that uses JWT (JSON Web Token) authentication for its REST API. The vulnerability stems from improper session termination (CWE-613: Insufficient Session Expiration). When users authenticated to Airflow's web interface and logged out, the application failed to add the JWT to a revocation list or otherwise mark it as invalid. JWTs are cryptographically signed tokens that typically include an expiration timestamp but no server-side state. Without explicit invalidation mechanisms like token blacklisting or database-backed session tracking, a valid JWT remains usable until its built-in expiration time passes. The affected CPE (cpe:2.3:a:apache:airflow) covers versions 3.0.0 through 3.1.x. Airflow 3.2.0 introduced a token invalidation mechanism, likely implemented via the referenced GitHub pull requests 56633 and 61339, which may use Redis-backed token blacklisting, database session tables, or JTI (JWT ID) tracking to prevent reuse of logged-out tokens.
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Severity by source
AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N
Primary rating from Vendor (apache) · only source for this CVE.
CVSS VectorVendor: apache
Lifecycle Timeline
3DescriptionCVE.org
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.
Blast Radius
ecosystem impact- 4 pypi packages depend on apache-airflow (2 direct, 2 indirect)
Ecosystem-wide dependent count for version 3.0.0.
Executive ViewAI
Apache Airflow versions 3.0.0 through 3.1.x contain a critical session management flaw where JWT tokens remain valid after user logout, enabling attackers with intercepted credentials to maintain unauthorized API access to workflow orchestration systems. Organizations running affected Airflow versions face risk of persistent unauthorized access to sensitive data pipelines and operational workflows, particularly in environments where tokens may be exposed through logs, network captures, or compromised systems.
Apply vendor patch: Apache Airflow 3.2.0. If immediate patching is not feasible: implement network-level API gateway with token revocation lists (blacklist/denylist) that intercepts and validates JWT tokens independent of Airflow; enforce short-lived token expiration (< 15 minutes) with mandatory re-authentication; implement continuous monitoring and alerting on token usage patterns post-logout; restrict Airflow API access to internal networks only pending patch deployment.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Information disclosure occurs when an application unintentionally exposes sensitive data that aids attackers in reconnaissance or directly compromises security.
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EUVD-2025-209371
GHSA-c92r-g8j5-vhcx
NVD
CVE.org
EPSS
Vulnrichment
VulDB
Exploit-DB