Apache Druid Remote Code Execution Scanner

Apache Druid is an open-source, high-performance, real-time analytics database that is used by many organizations to power their modern analytics applications. Built for scalably ingesting large amounts of data, Druid is used by developers, data scientists, and analysts to query streaming and batch data in milliseconds. It supports a wide range of industries including finance, telecommunications, media, and more, providing deep insights for decision making. The product is compatible with cloud and on-premises environments, offering flexibility for deployment. Often embedded in customer-facing applications, it empowers businesses to build data-driven and interactive experiences. Apache Druid's robust architecture ensures high availability, making it a popular choice for mission-critical applications.

Remote Code Execution (RCE) is a serious vulnerability that allows attackers to execute arbitrary commands or code on a targeted server or application. The vulnerability in Apache Druid is associated with the use of the Log4j library, which improperly handles certain input data, leading to potential exploitation. Attackers can craft special payloads that make servers execute code hosted in a location they control. This type of vulnerability poses significant risk because it can allow attackers to gain full control over the affected systems. The severity of this vulnerability is reflected in its ability to impact data confidentiality, integrity, and availability massively. It is critical for organizations to quickly identify and mitigate this threat to minimize the attack surface.

The technical vulnerability in Apache Druid stems from improper input handling in JNDI lookups by the Log4j library. The vulnerable endpoint is any service within the application that logs input data, which could be exploited by sending specially crafted requests. These requests can include URLs that trigger a remote server to execute code, leading to RCE. Common parameters targeted include user input fields that are logged without proper sanitization. The exploitation is often achieved through manipulating logging behavior to process malicious inputs, which contact external servers hosting the attacker-controlled code. This breach can eventually lead to system compromise and data theft. Organizations should ensure logging practices are updated to mitigate this flaw.

Exploitation of this vulnerability could lead to unauthorized access and control over affected systems, data exfiltration, and potential data manipulation. Malicious actors can deploy malware, create backdoors for persistent access, or manipulate data for fraud. Such attacks can disrupt business operations, leading to financial loss and reputational damage. In severe cases, it could lead to full-scale compromise of networks where Apache Druid is deployed. These outcomes stress the importance of timely detection and remediation to protect sensitive data and maintain operational integrity. The potential ripple effect on other systems within an organization's infrastructure underscores the critical nature of addressing this issue promptly and comprehensively.

REFERENCES

• https://www.cve.org/CVERecord?id=CVE-2021-44228
• https://logging.apache.org/log4j/2.x/security.html