CVE-2019-7144 in Acrobat Reader
Summary
by MITRE
Adobe Acrobat and Reader versions 2019.010.20100 and earlier, 2019.010.20099 and earlier, 2017.011.30140 and earlier, 2017.011.30138 and earlier, 2015.006.30495 and earlier, and 2015.006.30493 and earlier have an out-of-bounds read vulnerability. Successful exploitation could lead to information disclosure .
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Analysis
by VulDB Data Team • 06/14/2024
Adobe Acrobat and Reader applications contain a critical out-of-bounds read vulnerability that affects multiple versions across different release cycles. This vulnerability stems from insufficient bounds checking within the software's handling of PDF files, specifically when processing certain embedded objects or streams. The flaw allows an attacker to craft malicious PDF documents that trigger memory access violations when the vulnerable software attempts to read data beyond allocated memory boundaries. The vulnerability is classified as CWE-129, representing an insufficient bounds check, which is a fundamental security weakness that can lead to unpredictable behavior and information disclosure. According to the ATT&CK framework, this represents a software exploitation technique where adversaries leverage application flaws to gain unauthorized access to system resources.
The technical implementation of this vulnerability occurs during the parsing of PDF content where the application fails to properly validate array indices or buffer sizes before accessing memory locations. When a maliciously crafted PDF document is opened, the software's parser attempts to read data from memory locations that have not been properly validated, potentially exposing sensitive information from adjacent memory regions. This out-of-bounds read condition can result in the disclosure of stack contents, heap data, or other sensitive information that may contain credentials, encryption keys, or system memory patterns. The vulnerability is particularly concerning because it can be exploited through social engineering attacks where users unknowingly open malicious PDF files, making it a significant threat vector in targeted attacks.
The operational impact of this vulnerability extends beyond simple information disclosure, as it can serve as a stepping stone for more sophisticated attacks. Attackers can leverage the information disclosure to gather intelligence about the target system, potentially identifying memory layout patterns that aid in bypassing security mitigations like ASLR. The vulnerability affects a wide range of Adobe Acrobat and Reader versions, making it a persistent threat across multiple years of software releases. This widespread impact means that organizations with older software installations remain at risk, particularly those that have not implemented proper patch management processes. The vulnerability's exploitation does not require user interaction beyond opening the malicious file, making it particularly dangerous in phishing campaigns or targeted attacks where the attacker can deliver the payload through email attachments or web downloads.
Organizations should prioritize immediate patching of affected Adobe Acrobat and Reader installations to mitigate this vulnerability. Adobe released security updates for all supported versions, and system administrators should implement these patches as soon as possible. Additional mitigations include implementing strict file validation policies, deploying sandboxing solutions for PDF processing, and configuring email filters to block suspicious PDF attachments. Network segmentation and monitoring for unusual PDF-related activity can also help detect potential exploitation attempts. The vulnerability highlights the importance of maintaining up-to-date software and implementing comprehensive vulnerability management processes. Security teams should also consider implementing behavioral analysis tools that can detect anomalous PDF processing patterns that may indicate exploitation attempts. Regular security assessments and penetration testing should include evaluation of document processing capabilities to identify similar vulnerabilities in other software applications.