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medium·Exposed Panels·Updated Oct 8, 2024

Dokuwiki Panel Detection Scanner

This scanner detects the use of Dokuwiki login panel in digital assets.

Est. Time~10 seconds
Scan TypeSingle Scan
Targetsurl
CostFree
2.5k
Times Used
continuous scan runs
3.7k
Continuously Checked
assets under CS
2
Vulnerabilities Found
confirmed findings
References
Detail

Dokuwiki is a widely used open-source wiki software application designed primarily for documentation and collaboration purposes within organizations. It is predominantly used by technical writers, teams working on collaborative projects, and communities that need to document information seamlessly. Dokuwiki provides a simple and easy-to-understand syntax, which makes it an attractive choice for those looking to have a wiki setup without the need for extensive technical expertise. The software is utilized globally across various sectors such as education, healthcare, and software development. As it is a web-based application, it offers flexibility and accessibility, allowing users to manage content from anywhere. Its extensible nature through plugins also provides adaptability to fit diverse organizational needs.

The vulnerability addressed in this scenario is panel detection, which involves identifying the presence of a Dokuwiki login panel. This vulnerability doesn't directly impact security but constitutes an information leakage where attackers can identify the presence of Dokuwiki in the digital assets. Knowing the software in use can give malicious actors insights into further avenues of attack or exploitation, especially if the software version in use has known vulnerabilities. Identifying the login panel confirms the attack surface, allowing attackers to focus their efforts on gaining unauthorized access. Although the panel detection itself is informational, it becomes crucial as the first step for attackers in gathering information to launch potential attacks. Thus, awareness and mitigation of this vulnerability play a role in strengthening security postures.

Technically, the Dokuwiki panel detection occurs by sending a GET request to the Dokuwiki URL path, which generally includes identifiers like "/doku.php". When accessed, if the HTTP response status code is 200 and the body contains elements such as "dokuwiki__header" or "content=\"DokuWiki\"", a positive detection is made. This method uses simple yet effective checks based on HTML content patterns specific to Dokuwiki, ensuring the detection mechanism is accurate. By confirming the presence of these elements, the tool asserts the presence of a Dokuwiki login panel. Such details highlight that even subtle information like response codes and specific HTML markers can be leveraged to ascertain the software running on a server. Understanding these technical aspects emphasizes the importance of not leaving URL paths publicly exposed or unguarded.

If exploited, detecting the Dokuwiki panel does not directly lead to a security breach but increases the risk profile by exposing more information about the infrastructure. Potentially malicious actors could use this information to tailor attacks if they find vulnerabilities or misconfigurations within Dokuwiki. Subsequent attacks might involve brute force attempts to access the login panel, phishing for credentials, or exploiting weaknesses in outdated Dokuwiki versions. It can lead to unauthorized information access, system manipulation, or data manipulation risks. Therefore, preventing or obscuring the existence of such login panels can reduce these risks significantly.

REFERENCES

Solution Advice
  • Implement access controls to restrict access to the Dokuwiki login panel to only trusted IPs or internal networks.
  • Consider renaming or relocating the panel URL to a non-default path to reduce easy detection.
  • Enforce strong password policies and implement CAPTCHA to mitigate brute force attacks on the login page.
  • Regularly update Dokuwiki to the latest version to mitigate any potential vulnerabilities.
  • Monitor and log access attempts to the login panel to identify any unauthorized access efforts quickly.

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