CVE-2025-54941 is an OS command injection vulnerability classified under CWE-78 found in Apache Airflow version 3.0.0, specifically within the example DAG named `example_dag_decorator`. The root cause is the improper neutralization of special elements in a parameter that is not validated correctly, allowing a malicious UI user to manipulate the DAG to redirect execution to a malicious server. This redirection can lead to arbitrary code execution on the Airflow worker nodes, which are responsible for running scheduled workflows and tasks. The vulnerability requires that example DAGs be enabled in production environments, which is not the default configuration, or that the vulnerable example DAG code is copied and adapted into custom DAGs. The flaw allows an attacker with UI access to escalate privileges and execute OS commands, potentially compromising the confidentiality, integrity, and availability of the Airflow environment and the workflows it manages. Although no exploits have been observed in the wild, the vulnerability is significant due to the critical role Airflow plays in orchestrating data pipelines and business processes. The Apache Software Foundation addressed this issue in Airflow version 3.0.5 by implementing proper validation and sanitization of the affected parameters. Organizations using the `example_dag_decorator` or similar custom DAGs based on it should urgently review their code and upgrade to the patched version to mitigate this risk.

For European organizations, this vulnerability could have severe consequences, especially for those relying on Apache Airflow for critical data processing, ETL pipelines, and automated workflows. Successful exploitation could lead to remote code execution on worker nodes, enabling attackers to manipulate workflows, exfiltrate sensitive data, disrupt business operations, or pivot to other internal systems. This could impact sectors such as finance, healthcare, manufacturing, and telecommunications, where Airflow is used to automate complex data workflows. The compromise of Airflow infrastructure could also undermine regulatory compliance with GDPR and other data protection laws due to potential data breaches or unauthorized data processing. Additionally, the disruption of automated workflows could cause operational downtime and financial losses. Given that exploitation requires UI access and enabling example DAGs in production, the risk is somewhat mitigated by default configurations, but organizations that customize or enable example DAGs remain vulnerable.

1. Immediately review all deployed DAGs to identify any usage of the `example_dag_decorator` or DAGs derived from it. 2. Upgrade Apache Airflow installations to version 3.0.5 or later, where the vulnerability is patched. 3. Disable example DAGs in production environments unless absolutely necessary, as they are not intended for production use. 4. Implement strict access controls on the Airflow UI to limit user permissions and prevent unauthorized DAG modifications or executions. 5. Conduct code reviews and static analysis on custom DAGs to detect unsafe parameter handling and command injection risks. 6. Monitor Airflow logs and worker nodes for unusual activity indicative of exploitation attempts. 7. Employ network segmentation and firewall rules to restrict Airflow worker node communications to trusted sources only. 8. Educate development and operations teams about secure DAG development practices and the risks of enabling example or untrusted DAGs in production.