CVE-2017-17636 in MLM Forced Matrix
Summary
by MITRE
MLM Forced Matrix 2.0.9 has SQL Injection via the news-detail.php newid parameter.
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Analysis
by VulDB Data Team • 09/13/2025
The vulnerability identified as CVE-2017-17636 affects MLM Forced Matrix version 2.0.9, a multi-level marketing software platform that facilitates network marketing operations. This particular weakness represents a critical security flaw that compromises the integrity and confidentiality of user data within the application's database. The vulnerability specifically manifests through the news-detail.php script which processes user input through the newid parameter, creating an avenue for malicious actors to exploit the system's database layer.
The technical implementation of this SQL injection vulnerability stems from inadequate input validation and sanitization within the application's backend processing logic. When the news-detail.php script receives the newid parameter from user input without proper sanitization, it directly incorporates this data into SQL query construction without appropriate escaping or parameterization mechanisms. This flaw falls under the Common Weakness Enumeration category CWE-89, which specifically addresses SQL injection vulnerabilities that occur when user-supplied data is improperly handled within database queries. The vulnerability allows attackers to manipulate the underlying database queries through crafted input sequences that can alter the intended execution flow of SQL commands.
The operational impact of this vulnerability extends beyond simple data exposure, potentially enabling attackers to execute arbitrary database commands with the privileges of the application's database user. An attacker could leverage this vulnerability to extract sensitive information including user credentials, personal data, financial records, and business intelligence. The attack surface is particularly concerning given that MLM platforms typically handle extensive user information including contact details, transaction histories, and hierarchical network structures that could be exploited for further attacks. This vulnerability could facilitate unauthorized access to the entire database, potentially leading to complete system compromise and data exfiltration.
Mitigation strategies for this vulnerability should prioritize immediate implementation of proper input validation and parameterized query execution throughout the application's codebase. The recommended approach involves implementing strict input sanitization measures that filter out potentially malicious characters and sequences, while also employing prepared statements and parameterized queries to ensure that user input cannot alter the intended structure of SQL commands. Additionally, the system should implement proper access controls and privilege management to limit the database user's capabilities, reducing the potential impact of successful exploitation. Network-level protections including web application firewalls and intrusion detection systems should be deployed to monitor and block suspicious database access patterns. Regular security assessments and code reviews should be conducted to identify and remediate similar vulnerabilities across the entire application ecosystem, following industry best practices established by frameworks such as the OWASP Top Ten and NIST cybersecurity guidelines. The vulnerability also aligns with ATT&CK technique T1190 which describes the exploitation of vulnerabilities in web applications to gain unauthorized access to systems and data resources.