CVE-2015-0916 in Cacti
Summary
by MITRE
SQL injection vulnerability in graph.php in Cacti before 0.8.6f allows remote authenticated users to execute arbitrary SQL commands via the local_graph_id parameter, a different vulnerability than CVE-2007-6035.
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Analysis
by VulDB Data Team • 03/31/2019
The CVE-2015-0916 vulnerability represents a critical SQL injection flaw discovered in the Cacti network monitoring system version 0.8.6f and earlier. This vulnerability specifically affects the graph.php component within the application, which serves as a core interface for generating network performance graphs and visualizations. The flaw enables authenticated remote attackers to manipulate database queries through the local_graph_id parameter, creating a pathway for arbitrary SQL command execution. Unlike CVE-2007-6035 which targeted different components, this vulnerability demonstrates the persistent nature of SQL injection threats in web applications that process user-supplied input without proper sanitization. The vulnerability exists due to insufficient input validation and improper parameter handling within the graph.php script, allowing malicious users with valid credentials to escalate their privileges and potentially gain unauthorized access to underlying database systems.
The technical exploitation of this vulnerability occurs when an authenticated user submits a malicious local_graph_id parameter value to the graph.php endpoint. The application fails to properly escape or validate this input before incorporating it into SQL queries, creating a classic SQL injection vector. Attackers can leverage this weakness to execute malicious SQL commands that may include data exfiltration, database modification, or even command execution on the underlying database server. The vulnerability's impact extends beyond simple data theft as it can enable attackers to manipulate the monitoring system's configuration, alter performance data, or potentially gain deeper system access depending on the database permissions assigned to the Cacti application. This type of vulnerability aligns with CWE-89 which categorizes SQL injection as a fundamental web application security flaw requiring proper input sanitization and parameterized queries.
The operational impact of CVE-2015-0916 is significant for organizations relying on Cacti for network monitoring and management. The vulnerability allows attackers to compromise the integrity and confidentiality of network performance data, potentially leading to false alerts, data manipulation, or complete system compromise. Since the vulnerability requires only authenticated access, it can be exploited by insiders or attackers who have obtained legitimate user credentials through social engineering, credential theft, or other means. The attack surface is particularly concerning for network administrators who may have elevated privileges within the Cacti system, as successful exploitation could provide access to sensitive network infrastructure data. Organizations using Cacti for critical infrastructure monitoring face heightened risk of operational disruption, compliance violations, and potential security breaches that could affect their entire network monitoring ecosystem.
Organizations should implement immediate mitigations including upgrading to Cacti version 0.8.6f or later, which contains patches addressing this vulnerability. Additionally, implementing proper input validation and parameterized queries within the application code can prevent similar issues from occurring in the future. Network segmentation and access control measures should be enforced to limit the scope of potential exploitation, while regular security audits and penetration testing can help identify other potential vulnerabilities. The vulnerability also underscores the importance of following secure coding practices and adhering to industry standards such as those defined in the OWASP Top Ten and MITRE ATT&CK framework, particularly focusing on command injection and privilege escalation techniques. Organizations should also consider implementing database activity monitoring and anomaly detection systems to identify potential exploitation attempts and maintain comprehensive audit logs for forensic analysis.