Cloudera Hue Default Login Scanner
This scanner detects the use of Cloudera Hue in digital assets. It aims to identify instances of default admin credentials being used, which can be a potential security risk.
Short Info
Level
High
Single Scan
Single Scan
Can be used by
Asset Owner
Estimated Time
1 minute
Time Interval
15 days 18 hours
Scan only one
Domain, IPv4
Toolbox
-
Cloudera Hue is an open-source Web interface for analyzing data with Hadoop and Cloud technologies. It's widely used by data engineers, data scientists, and analysts to simplify the process of accessing and managing data stored on big data clusters. Hue provides a consistent user experience across Hadoop services and various components. It offers tools for creating custom applications and improving workplace efficiency by enabling different job executions. Hue is particularly valued in large enterprises where managing vast amounts of data is crucial. However, using default credentials can expose the system to unauthorized access by attackers.
The vulnerability tested by this scanner is related to default login credentials, which can be a significant risk. Such credentials, if left unaltered, provide easy access to unauthorized users to sensitive administrative interfaces. This detection helps identify systems where default usernames and passwords are in use. Often overlooked during installation, default credentials can lead to unauthorized access. They comprise a critical security misconfiguration that can be exploited by attackers. Identifying this vulnerability helps safeguard systems against unauthorized interference.
The key technical aspect of this vulnerability is the presence of unchanged default admin login credentials that are accessible through known Hue endpoints. The vulnerable endpoint in this context is `/hue/accounts/login?next=/`. The scanner verifies the presence of default credentials like 'admin:admin' which, if successful, indicate a security misconfiguration. By utilizing a pitchfork attack method, it matches known credential patterns against login forms. Discovering such credentials implies the need for immediate corrective action. The presence of distinguishable CSRF tokens and session identifiers confirms valid authentication flows.
When left uncorrected, this vulnerability can have serious repercussions, such as unauthorized access to sensitive data. It provides attackers with an entry point to execute further exploits within the system. The misuse of privileged interfaces can lead to data theft, data corruption, or even network intrusion. As such, default login credentials open up attack vectors that compromise the integrity and confidentiality of data. This has potential cascading effects across systems and applications dependent on the vulnerable service.
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