In recent discoveries by Unit 42 researchers, new security vulnerabilities have been identified in the Azure Data Factory Apache Airflow integration. These vulnerabilities pose significant risks to organizations that utilize Azure Data Factory, as attackers can exploit these flaws to gain unauthorized write permissions to a directed acyclic graph (DAG) file or to leverage a compromised service principal. Although Microsoft has classified these vulnerabilities as low severity, their potential impact on cloud environments is substantial. Attackers could obtain shadow admin control over Azure infrastructure, leading to risks such as data exfiltration, malware deployment, and unauthorized data access. Unit 42’s research identified multiple issues, including misconfigured Kubernetes RBAC in the Airflow cluster and weak authentication for Azure’s internal Geneva service.
1. Craft a DAG File
The initial step in the attack scenario involved crafting a DAG file that opens a reverse shell to a remote server and runs automatically when imported into the system. This step is crucial as it sets the groundwork for gaining unauthorized access to the Airflow cluster. By opening a reverse shell, an attacker can establish a direct line of communication back to their server, thereby allowing them to execute commands and potentially gain further access into the system. Upon importing this crafted DAG file, the code executes automatically due to specific scheduling parameters like schedule_interval and start_date, causing the reverse shell to initiate immediately.
Upon execution, the malicious DAG file activates and communicates back to an external server, leveraging the network capabilities of the Airflow worker nodes. This step underscores how easily compromised DAG files can be used to breach the security of a data pipeline, illustrating the criticality of securing these files against unauthorized modification and insertion. The importance of monitoring and validating the integrity of DAG files in repositories cannot be overstated, as even a single tampered file can serve as a gateway for attackers.
2. Upload the DAG File
The next phase of the attack involves uploading the crafted DAG file to a private GitHub repository connected to the Airflow cluster. This action exploits the connectivity between Airflow and the version control system, where repositories serve as the source of DAG definitions. By injecting the malicious code within the repository, the attacker relies on the workflow orchestrator to import and execute this manipulated DAG file. This underscores the necessity for stringent access controls and continuous monitoring of repositories that interface with critical infrastructure.
In this case, maintaining a secure and verified environment for DAG files is imperative. Organizations should implement robust authentication mechanisms and ensure that the repositories are free from unauthorized access or misconfiguration. Moreover, regular audits and real-time monitoring could help detect and prevent such malicious activities, safeguarding against potential breaches stemming from manipulated DAG files. Effective controls for repository access are essential in limiting vulnerability exposure.
3. Airflow Imports and Runs
The attack progresses as Airflow imports and runs the malicious DAG file automatically from the connected Git repository. This automatic execution is enabled by the predefined configurations and trusted repository interfacing with the Airflow cluster. Upon execution, the malicious code within the DAG file activates the reverse shell, thereby giving the attacker cluster admin privileges due to a Kubernetes service account linked to an Airflow worker. This critical flaw highlights how default configurations and insufficient scrutiny of third-party integrations can open avenues for exploitation.
However, the configured automatic imports can be both a strength and a vulnerability. While they facilitate seamless operational workflows, they also pose significant security risks if the source is compromised. Ensuring strict repository hygiene and applying security validation checks on imported files is paramount. Furthermore, using stronger authentication methods and thoroughly reviewing service account permissions can mitigate risks and prevent such high-level breaches from occurring.
4. Gain Write Permissions
Attackers have multiple avenues to gain access and manipulate DAG files. One prominent method involves gaining write permissions to the storage account containing these files. This can be achieved by leveraging either a principal account with write permissions or a shared access signature (SAS) token for the files. SAS tokens are particularly concerning as they grant temporary but significant access to resources, allowing the attacker to alter the DAG files without maintaining long-term access. Once tampered with, the modified files lie dormant until the victim imports them, triggering the malicious actions embedded within.
Mitigating this risk requires a proactive approach. Organizations should enforce least privilege access policies, ensuring that write permissions are granted only when absolutely necessary. Regularly rotating access credentials and closely monitoring SAS token usage can also offer an additional layer of security. By establishing stringent oversight and control measures over access permissions, companies can better protect their DAG files from unauthorized modifications.
5. Gain Access to a Git Repository
Another method of gaining access to manipulate DAG files is by obtaining credentials to a Git repository through leakage or due to a misconfigured repository. Once an attacker has access, they can create a new malicious DAG file or modify an existing one. The attacker then waits for the system to automatically import the compromised code. This scenario underscores the vulnerabilities inherent in repository management, particularly when repositories are misconfigured or lack adequate security measures.
To counteract this threat, organizations must employ robust security practices for their repositories. This includes implementing multi-factor authentication, regular security audits, and ensuring that repositories are correctly configured according to best security practices. Additionally, real-time monitoring and alerting systems can provide early warnings if unauthorized changes are detected, thus enabling quicker responses to potential breaches. Ensuring the security of repositories is a critical component in protecting DAG files and, by extension, the overall data pipeline.
6. Run the File Automatically
Upon importing the malicious DAG file, it runs automatically, executing its payload. In the researchers’ scenario, this involved opening a reverse shell back to the attacker’s server using predefined parameters like schedule_interval and start_date. The reverse shell allows the attacker to communicate with the Airflow instance, which in this case, runs under the minimal permissions of a Kubernetes pod. This step demonstrated the importance of scrutinizing the configurations and permissions assigned to all components within the Airflow environment.
By executing the reverse shell, the attacker gains initial access into the system under the constraints of the pod’s permissions. This is a critical juncture where quick detection and response are essential to mitigate further damage. Monitoring for unusual activity and implementing stringent ingress and egress rules can greatly enhance the security posture of the system. Understanding the behavior of automated tasks and the permissions granted to different components is vital to preempt such attacks.
7. Inspect the Pod
After gaining the initial access via the reverse shell, the next logical step for an attacker involves inspecting the Kubernetes pod to discover any additional credentials or secrets that may be accessible. In this case, the inspection revealed a service account token mounted into the pod file system. This token’s network connectivity enabled the attacker to download Kubernetes’ command-line tool, Kubectl, to test their permissions comprehensively. Discoveries like these expose the importance of securing secrets and minimizing credential exposure within pods.
Upon testing the permissions with Kubectl, the researchers found that the service account used by the pod had cluster admin privileges. This revelation indicated a critical security flaw, granting full control over the entire cluster. The importance of reviewing and securing service account permissions to prevent unauthorized access and escalation cannot be overstated. Ensuring that secret management practices are stringent and that service accounts operate under the principle of least privilege is fundamental to securing Kubernetes environments against such vulnerabilities.
