CVE-2017-2966 in Acrobat Reader
Summary
by MITRE
Adobe Acrobat Reader versions 15.020.20042 and earlier, 15.006.30244 and earlier, 11.0.18 and earlier have an exploitable heap overflow vulnerability in the image conversion engine related to parsing malformed TIFF segments. Successful exploitation could lead to arbitrary code execution.
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Analysis
by VulDB Data Team • 09/01/2024
Adobe Acrobat Reader contains a critical heap overflow vulnerability in its image conversion engine that affects multiple version ranges including 15.020.20042 and earlier, 15.006.30244 and earlier, and 11.0.18 and earlier. This vulnerability specifically manifests when processing malformed TIFF segments during image conversion operations, creating a condition where an attacker can manipulate memory allocation patterns to overwrite adjacent heap memory regions. The flaw resides in the TIFF parsing logic within the image conversion engine, which fails to properly validate input data boundaries before performing memory operations. This vulnerability is classified as a heap-based buffer overflow under CWE-122 and represents a classic memory corruption issue that can be exploited through crafted malicious TIFF files. The vulnerability enables remote code execution when a victim opens a specially crafted document containing malformed TIFF segments, as the application attempts to convert these segments without proper bounds checking.
The operational impact of this vulnerability extends beyond simple code execution to encompass complete system compromise. Attackers can leverage this heap overflow to inject malicious code into the Acrobat Reader process memory space, potentially escalating privileges or establishing persistent backdoors. The vulnerability is particularly dangerous because it operates within a widely deployed application that processes documents from untrusted sources, making it a prime target for phishing campaigns and social engineering attacks. The exploitation chain typically involves crafting a malicious TIFF file with oversized or malformed segments that trigger the buffer overflow during normal document processing. This vulnerability aligns with ATT&CK technique T1203 by enabling privilege escalation through code injection, and T1059 by allowing execution of arbitrary commands within the application context. The memory corruption occurs at the heap level, making detection challenging as the overflow may not immediately crash the application but instead corrupt memory in ways that can be leveraged for further exploitation.
Mitigation strategies for CVE-2017-2966 must address both immediate remediation and long-term security posture improvements. The most effective immediate solution involves updating to Adobe Acrobat Reader versions that contain patches for this vulnerability, specifically versions 15.020.20043 and later, 15.006.30245 and later, and 11.0.19 and later. Organizations should implement strict document validation policies that prevent untrusted TIFF files from being processed, including disabling TIFF image processing entirely if not required for business operations. Network-based defenses should include content filtering solutions that can detect and block suspicious TIFF file attachments, particularly those with unusual segment structures or oversized metadata. Additionally, security teams should deploy application whitelisting controls to restrict execution of vulnerable versions of Acrobat Reader and implement memory protection mechanisms such as DEP and ASLR to make exploitation more difficult. The vulnerability demonstrates the importance of input validation and boundary checking in image processing libraries, highlighting the need for comprehensive security testing of parsing functions and memory management routines. Organizations should also consider implementing sandboxing techniques for document processing to contain potential exploitation attempts within isolated environments. Regular vulnerability assessments and penetration testing should be conducted to identify similar memory corruption issues in other applications that process untrusted image formats.