Skip to main content
CVE Vulnerability Database
Vulnerability Database/CVE-2025-68438

CVE-2025-68438: Apache Airflow Information Disclosure Flaw

CVE-2025-68438 is an information disclosure vulnerability in Apache Airflow that exposes sensitive values in the Rendered Templates UI. This article covers technical details, affected versions, impact, and mitigation.

Updated:

CVE-2025-68438 Overview

CVE-2025-68438 is an information disclosure vulnerability in Apache Airflow versions prior to 3.1.6. The flaw exposes sensitive values in cleartext through the Rendered Templates UI when rendered template fields in a DAG exceed the configured [core] max_templated_field_length. Serialization of these oversized fields used a secrets masker instance that excluded user-registered mask_secret() patterns. As a result, secrets were not reliably masked before truncation and display in the web interface. The issue is tracked under CWE-200: Exposure of Sensitive Information to an Unauthorized Actor.

Critical Impact

Authenticated and unauthenticated UI viewers with access to the Rendered Templates page may view cleartext secrets that should have been masked, including API keys, tokens, and credentials passed through DAG template fields.

Affected Products

  • Apache Airflow versions before 3.1.6
  • Deployments relying on user-registered mask_secret() patterns for secret masking
  • Airflow installations where DAG template fields exceed the max_templated_field_length threshold

Discovery Timeline

  • 2026-01-16 - CVE-2025-68438 published to NVD
  • 2026-01-21 - Last updated in NVD database

Technical Details for CVE-2025-68438

Vulnerability Analysis

Apache Airflow renders Jinja-templated fields at task execution time and persists the rendered output for display in the Rendered Templates UI. When rendered output exceeds the [core] max_templated_field_length limit, Airflow serializes and truncates the field before storage. The serialization path instantiated a secrets masker that did not load user-registered patterns added through mask_secret(). Truncation then occurred against unmasked content, leaving sensitive substrings in the persisted record.

The vulnerability falls under [CWE-200] and affects confidentiality but not integrity or availability. Network attack vector applies because the Rendered Templates UI is reachable over HTTP. Exploitation does not require authentication factors beyond what the deployment configures for the Airflow web interface.

Root Cause

The root cause is an incomplete masker instance used during serialization of oversized template fields. The default masker handled built-in patterns such as Connection and Variable secrets, but it omitted custom patterns registered through the mask_secret() API. Truncation logic processed the raw rendered string before any user-defined masking pass could redact it.

Attack Vector

An attacker with access to the Airflow web UI navigates to a task instance whose template fields exceeded max_templated_field_length. The Rendered Templates view returns the stored, truncated payload containing unmasked secrets. No code execution or privilege escalation is required. The disclosure is passive and persists until DAG runs are purged or the field is overwritten.

No public proof-of-concept exploit is available, and the vulnerability is not listed in the CISA Known Exploited Vulnerabilities catalog.

Detection Methods for CVE-2025-68438

Indicators of Compromise

  • Rendered Templates UI entries containing cleartext API keys, tokens, or passwords that should have been masked
  • DAG tasks where rendered template field length exceeds the configured max_templated_field_length value
  • Audit log entries showing access to /rendered-templates or task instance detail endpoints from unexpected accounts

Detection Strategies

  • Query the Airflow metadata database for rendered_task_instance_fields rows whose serialized values match known secret patterns such as AKIA[0-9A-Z]{16}, ghp_[A-Za-z0-9]{36}, or custom organizational tokens
  • Review web server access logs for repeated requests to rendered template endpoints, particularly from non-administrative users
  • Compare mask_secret() registrations in DAG code against masked output in the UI to identify gaps

Monitoring Recommendations

  • Alert on Airflow versions reported by the /version endpoint or airflow version command that match releases before 3.1.6
  • Forward Airflow webserver and scheduler logs to a centralized SIEM for correlation against secret-scanning rules
  • Enable Airflow audit logging for UI access events and review on a recurring cadence

How to Mitigate CVE-2025-68438

Immediate Actions Required

  • Upgrade Apache Airflow to version 3.1.6 or later as instructed in the Apache Mailing List Discussion
  • Rotate any credentials, API keys, or tokens that may have appeared in rendered template fields prior to upgrade
  • Restrict access to the Airflow web UI to authenticated administrators while remediation is in progress

Patch Information

The Apache Airflow project released version 3.1.6 to fix this issue. The patch ensures that the secrets masker used during serialization of oversized template fields includes user-registered mask_secret() patterns before truncation occurs. Refer to the OpenWall OSS Security Update for the upstream advisory.

Workarounds

  • Increase [core] max_templated_field_length so that rendered fields do not exceed the truncation threshold, reducing the code path that triggers the flaw
  • Avoid passing secrets directly through Jinja-templated fields; reference them via Connection or Variable objects that use built-in masking
  • Purge historical rendered template records from the Airflow metadata database after rotating any exposed credentials
bash
# Configuration example
# Upgrade Apache Airflow to 3.1.6 or later
pip install --upgrade "apache-airflow>=3.1.6"

# Verify installed version
airflow version

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

Default Legacy - Prefooter | Experience the World’s Most Advanced Cybersecurity Platform

Experience the Most Advanced Cybersecurity Platform

See how the world’s most intelligent, autonomous cybersecurity platform can protect your organization today and into the future.