Molgenis Panel Detection Scanner

Molgenis is a web-based data management platform that is widely used in research and healthcare settings for managing and analyzing data. It is deployed by institutions needing a robust, user-friendly interface for data handling. The software helps researchers in organizing complex datasets and performing data analyses. Molgenis is prominent in fields that require large-scale data management like genomics and epidemiology. Its ease of use and customization make it popular in both academic and commercial research environments. The platform supports collaboration among researchers by providing extensive data sharing and analysis capabilities.

The detection scanner identifies the presence of Molgenis panels exposed on digital assets. It checks for unauthorized and unexpected access to the Molgenis interface, particularly focusing on open panels that may not require authentication. By pinpointing panels, it aids in the detection of potential security misconfigurations. The scanner serves as a valuable tool in recognizing exposure risks associated with data platforms where sensitive data could be disclosed inadvertently. The primary target is ensuring that these interfaces are not publicly accessible without proper security measures.

The scanner employs HTTP requests to probe the base URL and specific API endpoints of a web asset. It searches for distinct identifiers in the webpage's body text that signify the presence of Molgenis, such as the version marker and welcome messages. A successful detection corresponds with an HTTP 200 status, indicating that the panel can be accessed inadvertently. The technical focus is on confirming the exposure of Molgenis by matching text specific to the platform in the response body. Once detected, these panels point to possible misconfigurations in access controls.

Exposed panels could allow unauthorized users to access sensitive data without authentication, leading to potential data breaches. Misconfiguration could result in information disclosure to malicious actors who might exploit the data for unlawful activities. Such exposures can also lead to reputational damage if research data or personal information is leaked. The risk is notably pronounced for institutions managing sensitive research or clinical datasets. Thus, securing these panels is critical to maintain data integrity and confidentiality in institutions relying on Molgenis.

REFERENCES

• https://molgenis.org/
• https://github.com/molgenis/molgenis-emx2