Sangria GraphQL Information Disclosure Scanner

Sangria is an open-source GraphQL implementation for Scala that is used to build GraphQL servers. It is employed by developers and organizations worldwide to facilitate the development of APIs by providing a flexible query language interface. Sangria stands out for its modularity, allowing developers to extend its capabilities by plugging in custom logic and integrations. It is typically used in web development environments for building scalable, type-safe GraphQL APIs. By enabling structured data queries and mutations, Sangria helps developers perform complex data interactions seamlessly. Its design aims to accommodate a growing ecosystem of clients over time, ensuring robust API management.

Information Disclosure in Sangria GraphQL is a vulnerability where sensitive information can be unintentionally exposed to unauthorized users. This can occur when debugging or error messages are displayed to the client, revealing details about the application's internal configurations or structures. Detecting such vulnerabilities is crucial as they can lead to potential exploitation by malicious actors. Attackers may use this information to map application behaviors, identify other vulnerabilities, or plan further attacks, including those targeting business logic or data exfiltration. Further examination and understanding of this vulnerability can help mitigate risk and prevent unauthorized disclosure of sensitive information. Identifying and resolving these issues notably enhance the security posture of web applications utilizing Sangria GraphQL.

The vulnerability detail of this detection lies in the Sangria GraphQL endpoint '/graphql' and similar query paths. An improper configuration or response handling will allow the application to return errors with detailed messages when unexpected or malformed requests are made. The stored queries would contain syntax errors like invalid inputs, which mistakenly return additional details regarding expected schemas or data. The scanner checks the status code of the responses and evaluates content types to ensure no HTML is rendered, which could inadvertently display sensitive information in error messages. Consequently, by simulating malformed GraphQL queries, the scanner confirms whether critical information is improperly exposed through diagnostic messages.

The potential effects of exploiting this information disclosure vulnerability include giving attackers insights into the application's internal logic or structure. Armed with this information, attackers can craft precise queries or use additional techniques to gain access to restricted areas or data within the application. They may also employ this knowledge to launch further attacks aimed at other vulnerabilities identified through the error messages. Aside from attackers, competitors or malicious insiders might misuse this information to undermine the company's products or services. The potential for significant data breaches and loss of user trust can have lasting repercussions on the business.

REFERENCES

• https://github.com/dolevf/graphw00f/blob/main/graphw00f/lib.py