CVE-2022-24288: Apache Airflow RCE Vulnerability

CVE-2022-24288 Overview

CVE-2022-24288 is an OS Command Injection vulnerability affecting Apache Airflow versions prior to 2.2.4. The vulnerability exists in certain example DAGs (Directed Acyclic Graphs) that fail to properly sanitize user-provided parameters. This allows authenticated attackers to inject and execute arbitrary operating system commands through the Airflow web UI.

Critical Impact

Authenticated attackers can achieve full system compromise by injecting malicious OS commands through unsanitized DAG parameters, potentially leading to complete confidentiality, integrity, and availability impact on the affected system.

Affected Products

• Apache Airflow versions prior to 2.2.4
• Systems running example DAGs with user-controllable parameters
• Airflow deployments with web UI access enabled

Discovery Timeline

• 2022-02-25 - CVE-2022-24288 published to NVD
• 2024-11-21 - Last updated in NVD database

Technical Details for CVE-2022-24288

Vulnerability Analysis

This vulnerability falls under CWE-78 (Improper Neutralization of Special Elements used in an OS Command), commonly known as OS Command Injection. The flaw originates from example DAGs shipped with Apache Airflow that accept user-provided parameters without adequate input sanitization before passing them to system shell commands.

When users interact with the Airflow web UI to trigger DAG runs, they can supply custom parameters. In vulnerable example DAGs, these parameters are concatenated directly into shell commands or passed to functions that execute OS-level operations. The lack of proper input validation enables attackers to break out of the intended command context and inject additional commands.

The network-accessible attack vector through the web interface, combined with the low complexity required for exploitation and the potential for complete system compromise, makes this a particularly concerning vulnerability for organizations running affected Airflow deployments.

Root Cause

The root cause is insufficient input sanitization in example DAG code. User-provided parameters from the web UI are incorporated into shell commands without proper escaping or validation. This allows shell metacharacters and command separators (such as ;, |, &&, or backticks) to be interpreted by the underlying shell, enabling command injection attacks.

Attack Vector

The attack is executed through the network via the Apache Airflow web UI. An authenticated attacker with access to trigger DAG runs can:

1. Navigate to an affected example DAG in the Airflow web interface
2. Trigger a DAG run with a custom parameter containing shell metacharacters
3. Include malicious commands within the parameter value
4. The unsanitized parameter is passed to the shell, executing the injected commands with the privileges of the Airflow worker process

The vulnerability mechanism involves user parameters being passed directly to shell execution contexts. When a malicious parameter like ; whoami ; or $(malicious_command) is submitted through the web UI, the shell interprets these as additional commands rather than literal string values. This enables arbitrary command execution on the server hosting the Airflow workers. For detailed technical information, refer to the Apache Thread Discussion.

Detection Methods for CVE-2022-24288

Indicators of Compromise

• Unusual process spawning from Airflow worker processes (e.g., shells, network utilities like curl, wget, or nc)
• Unexpected outbound network connections from Airflow infrastructure
• Anomalous DAG trigger events with suspicious parameter values containing shell metacharacters
• Log entries showing command execution errors or unexpected output in DAG run logs

Detection Strategies

• Monitor Airflow audit logs for DAG triggers with parameters containing shell metacharacters (;, |, &&, $(), backticks)
• Implement application-layer monitoring to detect abnormal parameter patterns in DAG run requests
• Deploy endpoint detection to identify unexpected child processes spawned by Airflow workers
• Review web server access logs for unusual POST requests to DAG trigger endpoints

Monitoring Recommendations

• Enable comprehensive logging for all DAG trigger events and parameter values
• Configure alerting for shell process creation by Airflow worker accounts
• Implement network monitoring for unexpected egress traffic from Airflow infrastructure
• Regularly audit DAG configurations and parameter handling in custom and example DAGs

How to Mitigate CVE-2022-24288

Immediate Actions Required

• Upgrade Apache Airflow to version 2.2.4 or later immediately
• Remove or disable all example DAGs from production environments
• Restrict access to the Airflow web UI to only authorized and trusted users
• Review custom DAGs for similar input sanitization issues

Patch Information

Apache has addressed this vulnerability in Airflow version 2.2.4. The fix includes proper sanitization of user-provided parameters in the affected example DAGs. Organizations should upgrade to this version or later to remediate the vulnerability. Additional details are available in the Apache Thread Discussion.

Workarounds

• Remove example DAGs from the $AIRFLOW_HOME/dags directory if upgrading is not immediately possible
• Implement a web application firewall (WAF) rule to block requests containing shell metacharacters in DAG parameters
• Restrict Airflow web UI access using network segmentation and authentication controls
• Deploy read-only access controls for non-administrative users until patches can be applied

# Remove example DAGs from Airflow installation
# Navigate to your Airflow DAGs folder and remove example DAGs
rm -rf $AIRFLOW_HOME/dags/example_*

# Alternatively, disable example DAGs loading in airflow.cfg
# Set the following in your airflow.cfg configuration file:
# load_examples = False