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In Apache Airflow 3, a new security model was implemented to make sensitive fields in Connections (like passwords) write-only, meaning only users with edit permissions could set them, but not view them afterward. The CVE-2025-XXXXX vulnerability in version 3.0.3 introduced a flaw where this masking was improperly applied. Users with only READ permissions on Connections could retrieve the unmasked, sensitive data by querying the REST API endpoints (/api/v1/connections) or by viewing the connection details in the web UI. This exposure bypassed the central security configuration AIRFLOW__CORE__HIDE_SENSITIVE_VAR_CONN_FIELDS, which was set to `True` by default but rendered ineffective. The underlying cause was an error in the permission checks and field serialization logic specific to the Airflow 3.0.3 release.
Platform: Apache Airflow
Version: 3.0.3
Vulnerability : Information Exposure
Severity: Moderate
date: 2024-09-26
Prediction: Patch expected 2024-10-03
What Undercode Say:
Querying the vulnerable API endpoint
curl -H "Authorization: Bearer <USER_TOKEN>" https://airflow.example.com/api/v1/connections
Example response snippet showing exposed password
{
"connection_id": "my_db",
"conn_type": "postgres",
"host": "db.example.com",
"login": "user",
"password": "plaintext_password_here",
"port": 5432
}
Airflow DAG snippet attempting to mask data (ineffective in 3.0.3)
from airflow.models import Connection
conn = Connection.get_connection_from_secrets("my_db")
print(conn.password) Could return plaintext with READ perms
How Exploit:
An attacker with a standard user account possessing READ permissions on Connections can programmatically extract all connection details, including secrets, via the API. This can lead to a full compromise of connected external systems like databases and cloud services.
Protection from this CVE:
Immediately upgrade to Apache Airflow version 3.0.4 or later. Verify the configuration `AIRFLOW__CORE__HIDE_SENSITIVE_VAR_CONN_FIELDS=True` is set. As a temporary mitigation, review and restrict user permissions, limiting Connection READ access to only strictly necessary personnel.
Impact:
Exposure of credentials and connection strings stored in Airflow, potentially leading to unauthorized access to integrated databases, APIs, and other critical backend services.
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Sources:
Reported By: github.com
Extra Source Hub:
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