CVE-2017-11267 in Acrobat Reader
Summary
by MITRE
Adobe Acrobat Reader 2017.009.20058 and earlier, 2017.008.30051 and earlier, 2015.006.30306 and earlier, and 11.0.20 and earlier has an exploitable memory corruption vulnerability in the image conversion engine when processing Enhanced Metafile Format (EMF) private data interpreted as JPEG data. Successful exploitation could lead to arbitrary code execution.
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Analysis
by VulDB Data Team • 08/31/2024
This vulnerability resides within Adobe Acrobat Reader's image conversion engine, specifically when processing Enhanced Metafile Format files that contain private data incorrectly interpreted as JPEG data. The flaw represents a classic buffer overflow condition that occurs during the parsing of malformed image data, allowing attackers to manipulate memory layout and execute arbitrary code on affected systems. The vulnerability affects multiple versions of Adobe Acrobat Reader including 2017.009.20058 and earlier, 2017.008.30051 and earlier, 2015.006.30306 and earlier, and 11.0.20 and earlier, indicating a widespread exposure across the product's lifecycle. The issue stems from improper input validation and memory management within the image processing pipeline where EMF private data structures are mishandled during JPEG decoding operations. This memory corruption vulnerability falls under the CWE-121 category of stack-based buffer overflow, though the actual implementation likely involves heap-based memory corruption due to the complex nature of image processing operations.
The operational impact of this vulnerability is significant as it enables remote code execution when victims open maliciously crafted EMF files through Adobe Acrobat Reader. Attackers can craft specially formatted EMF files containing malicious private data that, when processed by the vulnerable image conversion engine, triggers the memory corruption. This creates a high-severity threat vector that can be delivered through email attachments, web downloads, or malicious documents. The vulnerability's exploitability is enhanced by the fact that Adobe Acrobat Reader is widely deployed across enterprise environments, making it an attractive target for attackers seeking persistent access to networks. The attack chain typically involves social engineering to convince users to open malicious documents, followed by automatic processing of embedded EMF graphics that trigger the vulnerable code path.
From a threat modeling perspective, this vulnerability aligns with ATT&CK technique T1059.007 for command and script interpreter and T1203 for Exploitation for Client Execution, as it enables attackers to execute arbitrary code on victim systems through document processing. The vulnerability demonstrates how legacy image format processing code can contain critical security flaws that persist across multiple product versions, highlighting the importance of proper input validation and memory safety practices. Organizations should consider implementing application whitelisting policies to restrict execution of Adobe Acrobat Reader in high-risk environments, while also maintaining strict email filtering and sandboxing measures for document attachments. The vulnerability also underscores the need for regular patch management and the importance of validating third-party libraries and components used in document processing applications.
Mitigation strategies should include immediate deployment of vendor patches and updates, which address the memory corruption issue through proper input validation and memory boundary checks. Network segmentation and user access controls can limit the potential impact if exploitation occurs, while endpoint detection and response solutions should monitor for suspicious process creation patterns and memory access violations. Organizations should also implement security awareness training to reduce the likelihood of users opening malicious documents, and maintain comprehensive backup and recovery procedures to address potential compromise scenarios. The vulnerability serves as a reminder of the critical importance of secure coding practices in image processing libraries and the necessity of thorough security testing for all file format parsers, particularly those handling complex binary data structures like EMF files that contain embedded private data sections.