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Misconfigured Kubernetes RBAC in Azure Airflow Puts Entire Cluster at Risk of Exploitation



A recent discovery by cybersecurity researchers has revealed three security vulnerabilities in Microsoft's Azure Data Factory Apache Airflow integration, which could potentially grant an attacker access to sensitive data and allow them to execute malicious activities within the entire Airflow cluster. The flaws include misconfigured Kubernetes RBAC, a flawed Geneva service handling mechanism, and weak authentication for the service. Organizations relying on this cloud-based workflow management tool must take immediate action to rectify these vulnerabilities and protect their security posture.

  • The recent discovery of three security vulnerabilities in Microsoft's Azure Data Factory Apache Airflow integration has sent shockwaves through the industry.
  • The flaws, deemed low-severity by Microsoft, could potentially grant an attacker access to sensitive data and execute malicious activities within the entire Airflow cluster.
  • Exploiting these flaws could allow an attacker to gain persistent access to the entire Airflow cluster as a shadow administrator.
  • The vulnerabilities were identified in misconfigured Kubernetes RBAC, secret handling of Azure's internal Geneva service, and weak authentication for Geneva.
  • Organizations relying on this tool must take immediate action to rectify these vulnerabilities and ensure their security posture is protected.



  • The recent discovery of three security vulnerabilities in Microsoft's Azure Data Factory Apache Airflow integration by cybersecurity researchers at Palo Alto Networks Unit 42 has sent shockwaves through the industry. The flaws, which were deemed low-severity by Microsoft but have significant implications for organizations relying on this cloud-based workflow management tool, could potentially grant an attacker access to sensitive data and allow them to execute malicious activities within the entire Airflow cluster.

    The vulnerabilities in question – Misconfigured Kubernetes RBAC (Role-Based Access Control) in Airflow cluster, misconfigured secret handling of Azure's internal Geneva service, and weak authentication for Geneva – were identified by the researchers as being particularly concerning due to their potential for exploitation. While they may not have been deemed high-severity, their impact on the security posture of an organization relying on this tool cannot be overstated.

    According to Palo Alto Networks Unit 42, exploiting these flaws could allow an attacker to gain persistent access to the entire Airflow cluster as a shadow administrator. This means that once an attacker has gained access to the cluster, they can potentially conduct covert actions such as data exfiltration and malware deployment without being detected by standard security tools.

    The researchers noted that one of the initial access techniques involved crafting a directed acyclic graph (DAG) file and uploading it to a private GitHub repository connected to the Airflow cluster, or altering an existing DAG file. The end goal was to launch a reverse shell to an external server as soon as it's imported. To achieve this, the threat actor would have to first gain write permissions to the storage account containing DAG files by utilizing a compromised service principal or a shared access signature (SAS) token for the files.

    Alternatively, they could break into a Git repository using leaked credentials. Once an attacker has gained write access to the storage account, they can potentially download the Kubernetes command-line tool kubectl and take full control of the entire cluster by "deploying a privileged pod and breaking out onto the underlying node."

    The researchers also noted that another vulnerability in the Geneva service could be exploited to tamper with log data or send fake logs to avoid raising suspicion when creating new pods or accounts. This highlights the importance of carefully managing service permissions to prevent unauthorized access.

    The discovery comes as the Datadog Security Labs detailed a privilege escalation scenario in Azure Key Vault that could permit users with the Key Vault Contributor role to read or modify Key Vault contents, such as API keys, passwords, authentication certificates, and Azure Storage SAS tokens. The researchers noted that this vulnerability was particularly concerning because even though a user with the Key Vault Contributor role had no direct access to Key Vault data over a key vault configured with access policies, it was discovered that the role did come with permissions to add itself to Key Vault access policies and access Key Vault data.

    "The policy update could contain the ability to list, view, update and generally manage the data within the key vault," security researcher Katie Knowles said. "This created a scenario where a user with the Key Vault Contributor role could gain access to all Key Vault data, despite having no Role-Based Access Control permission to manage permissions or view data."

    Microsoft has since updated its documentation to emphasize the access policy risk and provided guidance on how organizations can limit contributor role access to key vaults under the Access Policy permission model.

    The development also follows the discovery of an issue with Amazon Bedrock CloudTrail logging that made it difficult to differentiate malicious queries from legitimate ones made to large language models (LLMs), thereby allowing bad actors to conduct reconnaissance without raising any alert. This highlights the growing importance of threat detection and monitoring in cloud environments.

    In conclusion, the misconfigured Kubernetes RBAC in Azure Airflow could expose the entire cluster to exploitation. Organizations relying on this tool must take immediate action to rectify these vulnerabilities and ensure that their security posture is protected.



    Related Information:

  • https://thehackernews.com/2024/12/misconfigured-kubernetes-rbac-in-azure.html


  • Published: Tue Dec 31 00:02:41 2024 by llama3.2 3B Q4_K_M













         


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