CVE-2019-8046 in Acrobat Reader
Summary
by MITRE
Adobe Acrobat and Reader versions, 2019.012.20035 and earlier, 2019.012.20035 and earlier, 2017.011.30142 and earlier, 2017.011.30143 and earlier, 2017.011.30142 and earlier, 2015.006.30497 and earlier, and 2015.006.30498 and earlier have a heap overflow vulnerability. Successful exploitation could lead to arbitrary code execution.
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Analysis
by VulDB Data Team • 10/02/2025
Adobe Acrobat and Reader applications contain a critical heap overflow vulnerability that affects multiple versions across different release cycles. This vulnerability stems from insufficient bounds checking during the processing of maliciously crafted pdf files, specifically when handling certain embedded objects or streams within the document structure. The flaw occurs in the memory management routines where the application fails to validate the size of data being copied into heap-allocated buffers, allowing an attacker to write beyond the allocated memory boundaries and potentially overwrite adjacent memory regions.
The technical implementation of this vulnerability involves the application's failure to properly validate input parameters when parsing pdf objects, particularly those related to embedded content or compressed streams. When a malicious pdf file is opened, the vulnerable code path attempts to copy data into a heap buffer without adequate size verification, leading to a heap-based buffer overflow condition. This type of vulnerability falls under the common weakness enumeration CWE-121, which categorizes heap-based buffer overflow conditions that occur when insufficient bounds checking allows data to be written beyond the allocated buffer space.
The operational impact of this vulnerability is severe as successful exploitation can result in arbitrary code execution within the context of the user running the vulnerable Adobe application. Attackers can craft malicious pdf documents that, when opened by an affected version of Acrobat or Reader, will trigger the heap overflow condition and allow remote code execution. This creates a significant threat vector for social engineering campaigns where users might be tricked into opening malicious attachments or visiting compromised websites hosting malicious pdf files. The vulnerability is particularly dangerous because it can be exploited through web-based attacks without requiring user interaction beyond opening the document, making it an attractive target for automated exploit delivery systems.
The attack surface for this vulnerability spans across multiple Adobe product versions, including the 2019, 2017, and 2015 release cycles, indicating a long-standing issue that has persisted across several major versions. This widespread impact suggests that the underlying memory management flaw was not adequately addressed in the codebase, and the vulnerability affects both desktop and mobile versions of the affected applications. Security researchers have noted that the exploitation of this vulnerability aligns with techniques described in the attack pattern taxonomy under ATT&CK technique T1203, which involves the exploitation of memory corruption vulnerabilities for privilege escalation and code execution. Organizations should prioritize immediate patching of all affected versions, as the vulnerability has been actively exploited in the wild, and remediation efforts should include endpoint detection and response solutions to identify potential exploitation attempts.
Mitigation strategies should include immediate deployment of Adobe's security patches for all affected versions, implementation of pdf file filtering at network perimeters, and user education regarding the dangers of opening unexpected pdf attachments. Network administrators should consider implementing sandboxing solutions for pdf processing and monitoring for suspicious file access patterns. The vulnerability demonstrates the importance of proper input validation and memory safety practices in software development, with implications for the broader security community's approach to handling untrusted data inputs in document processing applications.