Horizon Alert
Summary of the vulnerability and why it matters
A vulnerability in Apache Airflow could allow an attacker to execute arbitrary code on your systems by embedding malicious code into a DAG file. This issue could compromise the security of your API Server and Scheduler processes, potentially impacting your data orchestration capabilities. The main concern is confirming relevance and exposure given the nature of the affected technology.
- Malicious code can be run remotely.
- Attackers can control critical orchestration systems.
- Confirm relevance and exposure of Airflow systems.
Attack Path
How an attacker could exploit the issue
An attacker could compromise the API server or scheduler by embedding a malicious trigger within a Directed Acyclic Graph (DAG) file. When the server loads this serialized DAG, it would execute the attacker-controlled class path, leading to remote code execution. This bypasses security controls by allowing code that should only be authored by a trusted user to run within the core server processes.
- Requires attacker to author a DAG.
- Malicious DAG deserialization on server.
- Remote code execution on server.
Live Threat
Current exploitation, exposure, and threat context
A vulnerability in how serialized DAGs are processed could allow a malicious DAG author to execute arbitrary code on the API server or scheduler. This occurs when the Scheduler or API Server loads a serialized DAG that contains a specially crafted trigger. When supported by the advisory, this could affect the integrity and availability of the API Server and Scheduler processes.
- API Server/Scheduler process integrity.
- Malicious DAG author embeds malicious trigger.
- Remote code execution on server processes.
Operational Fix
Recommended remediation, mitigation, and detection steps
The Airflow platform owner or the application team responsible for managing DAGs and the Airflow API Server/Scheduler processes should take the lead on this vulnerability. The immediate first step is to identify all Airflow deployments, determine their exposure, and confirm which DAGs are sourced from untrusted authors or external inputs. Once identified and prioritized by risk, a remediation plan involving vendor coordination and maintenance window scheduling can be developed.
- Identify affected Airflow instances.
- Verify DAG author trust and exposure.
- Plan remediation based on risk.
