Webalizer Panel Detection Scanner

Webalizer is a web log analysis software that visualizes server statistics through a web-based interface. It is widely used by system administrators to track and analyze web traffic data and patterns. Suitable for individuals and organizations managing websites, it offers insights into page views, visit durations, and referring sites. Normally deployed on web servers, Webalizer aids in performance monitoring and optimization of websites. Its comprehensive analytical capability is utilized to enhance user experience and server management. Various hosting providers incorporate Webalizer as a tool in their hosting packages to provide users with accessible web statistics.

The vulnerability associated with the Webalizer panel is tied to unauthorized access detection. By identifying its presence, security teams can inspect if any web log data could be publicly exposed. This vulnerability can lead to potential information disclosure if access to the panel is not adequately protected. As it deals with web traffic data, ensuring this panel is shielded from unauthorized access is crucial. Detecting the Webalizer panel helps in addressing misconfigurations that might otherwise be exploited. This awareness is essential for maintaining data confidentiality and integrity.

The technical details involve the detection of the Webalizer panel endpoint using specific keywords like "Webalizer Version" and "Usage statistics for" in the webpage. The scanner checks for a 200 HTTP status code response, indicating the panel's accessibility. A regex extractor identifies the Webalizer version from the accessible interface. These checks are designed to detect unprotected instances of Webalizer that could be accessed publicly when the URL path '{{BaseURL}}/webalizer/' is not adequately secured. The use of specific content matchers ensures the detection's accuracy and relevance.

When exploited, this vulnerability could lead to the unauthorized access of web server analytics, providing attackers with insights into user behavior and server performance. It could expose sensitive information such as IP addresses and browsing patterns, posing privacy risks. Unauthorized users might leverage the information for targeted attacks or reconnaissance activities. The exploitation of this vulnerability compromises the confidentiality of analytics data. In commercial contexts, this information might represent a competitive disadvantage if accessed by rival entities.

REFERENCES

• https://www.exploit-db.com/ghdb/197