CVE-2022-34236 in Acrobat Reader
Summary
by MITRE • 07/15/2022
Adobe Acrobat Reader versions 22.001.20142 (and earlier), 20.005.30334 (and earlier) and 17.012.30229 (and earlier) are affected by an out-of-bounds read vulnerability that could lead to disclosure of sensitive memory. An attacker could leverage this vulnerability to bypass mitigations such as ASLR. Exploitation of this issue requires user interaction in that a victim must open a malicious file.
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Analysis
by VulDB Data Team • 08/01/2022
This vulnerability resides in Adobe Acrobat Reader's handling of malformed PDF files, specifically within the document parsing logic that processes embedded objects and streams. The out-of-bounds read occurs when the application attempts to access memory locations beyond the allocated buffer boundaries while processing certain PDF elements, particularly those involving compressed data streams or malformed object references. The flaw manifests when the reader encounters crafted PDF files that contain oversized or improperly formatted data structures, causing the application to read beyond intended memory boundaries. This type of vulnerability falls under the CWE-125 weakness category, which describes out-of-bounds read conditions that can expose sensitive information stored in adjacent memory locations.
The operational impact of this vulnerability extends beyond simple information disclosure, as it can be leveraged to defeat critical security mitigations such as Address Space Layout Randomization. When an attacker successfully triggers this out-of-bounds read, they can potentially extract memory addresses from the process heap, stack, or other sensitive areas, effectively leaking information that would normally be protected by ASLR. This memory disclosure capability significantly reduces the effectiveness of modern exploit mitigations, as the attacker can use the leaked addresses to construct more sophisticated attacks targeting specific memory locations. The vulnerability specifically affects multiple versions of Adobe Acrobat Reader, including the 2022 release, 2020 release, and 2017 release lines, indicating a long-standing issue that has persisted across several major version releases.
Exploitation of this vulnerability requires social engineering to convince a user to open a maliciously crafted PDF file, making it a typical attack vector for phishing campaigns or targeted attacks. The attack chain begins with the delivery of a specially crafted PDF document that contains the malformed data structures triggering the out-of-bounds read. Once opened, the reader's processing of the malicious content causes the application to read beyond its allocated memory boundaries, potentially exposing sensitive memory contents including stack canaries, heap metadata, or other security-relevant information. This type of attack aligns with the ATT&CK technique T1203, which involves the use of malicious files to execute code or extract information, and specifically demonstrates how application-level vulnerabilities can be exploited to bypass system security controls. The vulnerability represents a critical weakness in the application's input validation and memory management practices, as it fails to properly bounds-check data during PDF parsing operations.
The recommended mitigations for this vulnerability primarily focus on immediate software updates and user education. Adobe has released patches addressing this issue in newer versions of Acrobat Reader, which implement proper bounds checking and memory validation during PDF processing. Organizations should prioritize deployment of these security updates across all affected systems, particularly in environments where users may encounter untrusted PDF content. Additionally, implementing email filtering solutions and web proxies that scan PDF attachments for malicious content can provide additional layers of protection. Network administrators should consider implementing application whitelisting policies that restrict execution of untrusted PDF files, and users should be trained to avoid opening PDF attachments from unknown or untrusted sources. The vulnerability also highlights the importance of regular security assessments and penetration testing to identify similar memory safety issues in other applications, particularly those handling complex file formats with extensive parsing requirements.