CVE-2022-42406 in PDF-XChange Editor
Summary
by MITRE • 01/26/2023
This vulnerability allows remote attackers to disclose sensitive information on affected installations of PDF-XChange Editor. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of EMF files. Crafted data in an EMF file can trigger a read past the end of an allocated buffer. An attacker can leverage this in conjunction with other vulnerabilities to execute arbitrary code in the context of the current process. Was ZDI-CAN-18369.
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Analysis
by VulDB Data Team • 04/29/2025
CVE-2022-42406 represents a critical buffer over-read vulnerability affecting PDF-XChange Editor software that falls under the Common Weakness Enumeration category CWE-125, which defines "Out-of-Bounds Read" conditions. This vulnerability specifically manifests during the parsing of EMF (Enhanced Metafile) files, a graphics format commonly used for storing device-independent vector graphics. The flaw occurs when the application processes maliciously crafted EMF files that contain data structures designed to trigger memory access beyond the bounds of allocated buffer regions. This type of vulnerability is particularly dangerous as it can lead to information disclosure and potentially arbitrary code execution within the context of the current process, making it a prime target for exploitation by threat actors.
The technical exploitation of this vulnerability requires user interaction through either visiting a malicious webpage that loads the crafted EMF file or opening a malicious file directly within the PDF-XChange Editor application. This user interaction requirement places the vulnerability in the ATT&CK framework category of initial access through social engineering or malicious file delivery techniques. When a user engages with the malicious content, the EMF parser fails to properly validate buffer boundaries during data processing, resulting in a read past the end of an allocated buffer. This memory access violation can expose sensitive data from adjacent memory locations, potentially revealing stack contents, heap data, or other critical application information that could aid in further exploitation attempts.
The operational impact of CVE-2022-42406 extends beyond simple information disclosure to encompass potential privilege escalation and system compromise scenarios. Attackers can leverage this vulnerability as a stepping stone for more sophisticated attacks, potentially combining it with other vulnerabilities to achieve arbitrary code execution. The vulnerability's presence in a widely-used document editing application means that successful exploitation could affect numerous enterprise environments where PDF-XChange Editor is deployed. Organizations running affected versions of the software face significant risk of data breaches, as the information disclosure could expose sensitive application memory structures that might contain authentication tokens, user credentials, or other confidential data. The vulnerability's classification as ZDI-CAN-18369 indicates it was identified through coordinated disclosure channels, highlighting the severity and potential widespread impact.
Mitigation strategies for CVE-2022-42406 should focus on immediate patch management and operational security enhancements. Organizations should prioritize updating PDF-XChange Editor to the latest version that addresses this vulnerability, as provided by the vendor. Network defenders should implement content filtering measures to block suspicious EMF files and monitor for unusual file access patterns that might indicate exploitation attempts. The vulnerability's nature makes it particularly susceptible to defense-in-depth approaches, including application whitelisting, sandboxing of document processing, and regular security assessments of document handling capabilities. Additionally, security teams should conduct user awareness training to recognize potentially malicious content that might trigger this vulnerability, as the requirement for user interaction means social engineering remains a critical attack vector. Implementing proper input validation and bounds checking in the application's EMF parsing routines would prevent this vulnerability from being exploited, aligning with industry best practices for secure coding standards and reducing the attack surface for similar buffer overflow conditions.