CVE-2011-2397 in Connected Backup
Summary
by MITRE
The Agent service in Iron Mountain Connected Backup 8.4 allows remote attackers to execute arbitrary code via a crafted opcode 13 request that triggers use of the LaunchCompoundFileAnalyzer class to send request data to the System.getRunTime.exec method.
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Analysis
by VulDB Data Team • 01/26/2018
The vulnerability identified as CVE-2011-2397 resides within the Iron Mountain Connected Backup 8.4 Agent service, representing a critical remote code execution flaw that fundamentally compromises system integrity. This vulnerability specifically targets the service's handling of incoming network requests through a carefully crafted opcode 13 message that exploits a dangerous code execution pathway. The flaw manifests when the system processes this particular opcode and subsequently invokes the LaunchCompoundFileAnalyzer class, which then forwards the malicious request data to the System.getRuntime().exec method, creating an exploitable chain that allows remote attackers to execute arbitrary commands on the affected system with the privileges of the running service.
The technical exploitation of this vulnerability follows a well-defined attack pattern that aligns with common remote code execution vectors. The LaunchCompoundFileAnalyzer class serves as the primary attack vector by accepting untrusted input from network requests without proper validation or sanitization. When opcode 13 is received, the system fails to properly validate the incoming data structure, allowing malicious input to flow directly into the system's execution engine. This design flaw directly violates security principles of input validation and privilege separation, as the system treats potentially malicious data as executable commands rather than mere data. The use of System.getRuntime().exec represents a particularly dangerous approach to command execution since it allows arbitrary shell command injection, bypassing typical application-level security controls.
From an operational impact perspective, this vulnerability presents a severe threat to organizations relying on Iron Mountain Connected Backup services, as it enables complete system compromise from remote locations without requiring authentication. The attack surface extends beyond individual hosts to potentially affect entire backup infrastructures, as successful exploitation could allow attackers to access, modify, or exfiltrate backed-up data while simultaneously establishing persistent access points. The vulnerability's remote nature means that attackers can exploit it from anywhere on the internet, making it particularly dangerous for organizations with exposed backup services. This flaw essentially transforms the backup service from a legitimate data protection mechanism into a potential entry point for broader network infiltration, as demonstrated by the typical attack patterns documented in the attack tree framework.
Mitigation strategies for this vulnerability must address both immediate remediation and long-term architectural improvements. Organizations should immediately apply available patches or updates from Iron Mountain to address the specific flaw in the Agent service implementation. The recommended approach involves implementing proper input validation and sanitization within the LaunchCompoundFileAnalyzer class, ensuring that all incoming opcode requests undergo rigorous verification before any processing occurs. Additionally, network segmentation should be implemented to restrict access to the backup service ports, following the principle of least privilege as outlined in cybersecurity frameworks. The vulnerability's characteristics align with CWE-77 and CWE-78 categories, which specifically address command injection flaws and improper input handling respectively, making these standards valuable references for implementing comprehensive defensive measures. Security monitoring should be enhanced to detect anomalous patterns in backup service communications, as the exploitation of this vulnerability typically generates unusual network traffic that can be identified through proper log analysis and anomaly detection systems.