CVE-2017-15720 in Airflow
Summary
by MITRE
In Apache Airflow 1.8.2 and earlier, an authenticated user can execute code remotely on the Airflow webserver by creating a special object.
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Analysis
by VulDB Data Team • 05/05/2020
Apache Airflow represents a powerful workflow management platform that enables users to programmatically author, schedule, and monitor data pipelines through a web-based interface. The vulnerability identified as CVE-2017-15720 resides within the webserver component of Airflow versions 1.8.2 and earlier, where an authenticated user possesses the capability to execute arbitrary code remotely. This flaw stems from insufficient input validation and sanitization within the object creation mechanisms that Airflow employs for task definitions and DAG configurations. The vulnerability specifically exploits the deserialization process that occurs when Airflow processes user-supplied data structures, allowing maliciously crafted objects to be interpreted and executed by the webserver with elevated privileges.
The technical exploitation of this vulnerability requires an authenticated user account within the Airflow system, which significantly reduces the attack surface compared to unauthenticated exploits. However, the impact remains severe as the authenticated user can leverage this weakness to execute arbitrary commands on the webserver host. The vulnerability falls under CWE-502 which describes "Deserialization of Untrusted Data" and aligns with ATT&CK technique T1059.001 for command and scripting interpreter. When an attacker successfully exploits this vulnerability, they can gain full control over the webserver, potentially leading to data exfiltration, privilege escalation, or the deployment of additional malicious payloads. The attack vector typically involves creating a malicious DAG file or task definition that contains serialized objects designed to trigger code execution upon deserialization by the vulnerable Airflow webserver.
The operational impact of this vulnerability extends beyond immediate code execution capabilities to encompass broader system compromise and data integrity threats. Organizations utilizing affected Airflow versions face significant risk as the vulnerability allows attackers to manipulate the underlying data pipeline infrastructure and potentially access sensitive data processed through these workflows. The authenticated nature of the exploit means that attackers typically need to obtain valid credentials through social engineering, credential theft, or other means of unauthorized access. This vulnerability particularly affects data analytics environments where Airflow is used to orchestrate critical business processes, making it attractive to adversaries seeking to disrupt operations or extract valuable information. The impact is compounded by the fact that Airflow webserver processes often run with elevated privileges necessary to execute workflow tasks, providing attackers with potential access to underlying system resources and databases.
Mitigation strategies for CVE-2017-15720 primarily focus on immediate version upgrades to Airflow 1.9.0 or later where this vulnerability has been addressed through enhanced input validation and secure deserialization practices. Organizations should implement strict access controls and monitor user activities within their Airflow environments to detect anomalous behavior indicative of exploitation attempts. The principle of least privilege should be enforced by ensuring that Airflow webserver processes operate with minimal required permissions and that user accounts have only necessary access rights. Security monitoring solutions should be configured to detect suspicious DAG file uploads or task definitions that might contain malicious serialization patterns. Additionally, regular security assessments and penetration testing of Airflow environments can help identify potential weaknesses in access controls and input validation mechanisms. Organizations should also consider implementing network segmentation to limit access to Airflow webserver components and establish robust backup and recovery procedures to ensure business continuity in case of successful exploitation attempts.