CVE-2018-16022 in Acrobat Reader
Summary
by MITRE
Adobe Acrobat and Reader versions 2019.008.20081 and earlier, 2019.008.20080 and earlier, 2019.008.20081 and earlier, 2017.011.30106 and earlier version, 2017.011.30105 and earlier version, 2015.006.30457 and earlier, and 2015.006.30456 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 • 08/04/2024
This vulnerability resides in Adobe Acrobat and Reader software across multiple versions, specifically affecting releases up to and including 2019.008.20081, 2017.011.30106, 2015.006.30457, and their respective earlier counterparts. The core issue manifests as an out-of-bounds read condition that occurs when processing maliciously crafted PDF files. This type of vulnerability falls under the CWE-125 category of out-of-bounds read, which represents a fundamental memory safety issue where an application attempts to access memory locations beyond the allocated buffer boundaries. The vulnerability stems from insufficient input validation and boundary checking mechanisms within the PDF parsing engine, particularly when handling complex or malformed embedded objects within PDF documents. Attackers can exploit this weakness by crafting specially designed PDF files that trigger the out-of-bounds memory access during document rendering or parsing operations. When successful, the exploitation leads to information disclosure, where sensitive data from adjacent memory locations may be read and potentially exfiltrated. This information disclosure can include fragments of other memory segments such as passwords, encryption keys, or other sensitive application data that happens to be stored in the adjacent memory regions. The operational impact extends beyond simple data leakage, as this vulnerability could potentially serve as a stepping stone for more sophisticated attacks, including privilege escalation or further exploitation attempts. The vulnerability affects a broad range of Adobe Acrobat and Reader versions, making it particularly concerning for enterprise environments where multiple versions may be in use simultaneously, and the attack surface remains expansive. Organizations with legacy systems running older versions face heightened risk due to the extended support windows and limited patch availability for older software releases. The vulnerability's exploitation requires user interaction, typically through opening a malicious PDF document, which aligns with common attack vectors described in the mitre ATT&CK framework under the initial access and execution phases. This makes social engineering campaigns particularly dangerous as they can leverage the trust users place in PDF documents to deliver payloads that trigger this out-of-bounds read condition. The information disclosure aspect of this vulnerability can be particularly damaging in environments where sensitive corporate or personal data is processed through Adobe Reader applications. The memory corruption patterns associated with out-of-bounds reads can also potentially lead to more severe consequences including application crashes or, in rare cases, arbitrary code execution depending on the memory layout and adjacent data structures. Security professionals should note that this vulnerability demonstrates the ongoing challenges in PDF processing engines and the critical importance of robust input validation and memory safety mechanisms. The widespread use of Adobe Reader across different operating systems and platforms means that this vulnerability can affect diverse computing environments, from individual workstations to enterprise document management systems. Organizations should prioritize immediate patching of affected versions to mitigate the risk of exploitation and implement additional security controls such as PDF sandboxing, content filtering, and user education to reduce attack surface. The vulnerability also highlights the importance of regular security assessments and vulnerability management programs to identify and remediate similar issues before they can be exploited by malicious actors.