CVE-2024-31750 Scanner

F-logic DataCube3 is a software platform utilized to streamline data operations, largely favored by businesses for efficient data analysis and management. It is primarily adopted in technologically driven environments where large datasets are manipulated for operational insights. Designed to improve data handling capabilities, it enables the automation of data fetching and analysis tasks. Its ease of integration with existing systems makes it appealing to corporations seeking to enhance their database management without significant infrastructure overhaul. With a robust architecture, DataCube3 is trusted to handle complex data operations across multiple domains. Despite its capabilities, maintaining security within its architecture remains paramount.

SQL Injection is a critical web security vulnerability that allows an attacker to interfere with the queries that an application makes to its database. It enables the attacker to view data that they are not normally able to retrieve, such as other users' data, other tables' structures, or sensitive system information. The vulnerability could allow malicious administrators or external attackers to execute unauthorized SQL commands within the database. The injection is facilitated by passing unexpected sequences of characters into the data fields exposed by the application. As a result, the invader could locate and extract pivotal information without the application's consent. It emphasizes the importance of securing application inputs to mitigate unauthorized database interactions.

The vulnerability in F-logic DataCube3 involves the manipulation of the 'req_id' parameter within SQL queries. By exploiting this parameter, attackers can utilize crafted SQL statements to trick the database into running unexpected commands. The identified point of exploitation is the 'getting_index_data.php' endpoint of the software. The compromise occurs via POST requests, which are altered with SQL payloads that disrupt normal query execution. The 'req_id' parameter is particularly susceptible to union-based SQL injection attacks, allowing for the retrieval of arbitrary database entries. By leveraging this flaw, attackers can bypass authentication bypasses to obtain sensitive data strategically.

If exploited, the SQL Injection vulnerability could lead to numerous detrimental effects on the vulnerable system. Attackers could steal sensitive information stored within the database, impacting user privacy and data security. They might also alter, delete, or corrupt existing data, adversely affecting the system’s integrity and availability. Furthermore, unauthorized data manipulation could allow attackers to escalate their privileges, gaining broader access to restricted database segments. The exploitation might result in reputational damage to organizations using the affected software, alongside financial losses due to data breaches. Rectifying these issues could require significant resources and increased cybersecurity measures.

REFERENCES

• https://github.com/lampSEC/semcms/blob/main/datacube3.md
• https://github.com/MrWQ/vulnerability-paper/blob/master/bugs/DataCube3%20getting_index_data.php%20SQL%20%E6%B3%A8%E5%85%A5%E6%BC%8F%E6%B4%9E.md
• https://nvd.nist.gov/vuln/detail/CVE-2024-31750
• https://github.com/wy876/POC