CVE-2023-22272 in RoboHelp Server
Summary
by MITRE • 11/17/2023
Adobe RoboHelp Server versions 11.4 and earlier are affected by an Improper Input Validation vulnerability that could lead to information disclosure by an unauthenticated attacker. Exploitation of this issue does not require user interaction.
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Analysis
by VulDB Data Team • 12/12/2023
Adobe RoboHelp Server version 11.4 and earlier contains a critical improper input validation vulnerability that exposes the system to unauthorized information disclosure. This vulnerability falls under CWE-20, which specifically addresses improper input validation flaws in software applications. The flaw exists in how the server processes incoming requests without adequate sanitization of user-supplied data, creating a pathway for malicious actors to extract sensitive information from the system. Attackers can exploit this weakness without requiring any user interaction or authentication credentials, making it particularly dangerous as it can be leveraged by anyone with network access to the affected server.
The technical implementation of this vulnerability stems from insufficient validation mechanisms within the server's request handling process. When RoboHelp Server receives HTTP requests, it fails to properly validate or sanitize input parameters that could contain malicious payloads. This allows an unauthenticated attacker to craft specific requests that bypass normal security controls and access internal system information. The vulnerability specifically impacts the server's ability to properly process file paths or parameter values, potentially enabling directory traversal attacks or direct information disclosure mechanisms. The lack of input validation creates a condition where attacker-controlled data can directly influence the server's behavior and output, leading to unauthorized data exposure.
The operational impact of this vulnerability extends beyond simple information disclosure, as it represents a fundamental security weakness that could enable more sophisticated attacks. An attacker who successfully exploits this vulnerability could potentially access sensitive configuration files, user data, or system documentation that should remain protected. This could lead to the exposure of internal network structures, authentication mechanisms, or other confidential information that would otherwise be restricted. The vulnerability's ease of exploitation, combined with its lack of requiring user interaction, makes it particularly attractive to automated attack tools and opportunistic threat actors who seek to maximize their impact with minimal effort. Organizations using affected versions of RoboHelp Server face significant risk of unauthorized data access and potential regulatory compliance violations.
Organizations should immediately implement mitigations to address this vulnerability by upgrading to Adobe RoboHelp Server version 11.5 or later, which contains the necessary patches to resolve the improper input validation issue. System administrators should also consider implementing network-level restrictions to limit access to RoboHelp Server instances, particularly when they are exposed to untrusted networks or the internet. Additional defensive measures include deploying web application firewalls to monitor and filter incoming requests, implementing proper input validation at the network perimeter, and conducting thorough security assessments of all RoboHelp Server deployments. The vulnerability's classification under ATT&CK technique T1213.002, which covers data from information repositories, indicates that organizations should also strengthen their overall data protection strategies and implement proper access controls to minimize the potential impact of such information disclosure events. Regular security monitoring and vulnerability scanning should be conducted to identify any remaining instances of the vulnerable software and ensure complete remediation across all affected systems.