CVE-2017-11260 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 a GIF image. 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 interpreted as GIF images. The flaw represents a classic memory corruption issue that arises from improper handling of image format conversions, where the software fails to properly validate or sanitize input data before processing. The vulnerability affects multiple versions of Adobe Acrobat Reader across different release cycles, indicating a persistent flaw in the image processing logic that has remained unaddressed for several years. The exploitation occurs when the application attempts to convert EMF private data into GIF format, triggering a buffer overflow or heap corruption that can be leveraged by malicious actors.
The technical implementation of this vulnerability stems from inadequate bounds checking and memory management within the image conversion pipeline. When Adobe Acrobat Reader encounters EMF files containing private data structures that resemble GIF image headers, the application's parser does not properly validate the data length or structure before attempting to copy or process the information into memory buffers. This creates opportunities for attackers to craft malicious EMF files that, when opened in the vulnerable software, cause memory corruption. The vulnerability can be categorized under CWE-121 as a stack-based buffer overflow, though the actual exploitation likely involves heap-based memory corruption due to the complex nature of image processing operations. The attack vector requires user interaction through opening a malicious document, making it a typical social engineering target.
The operational impact of this vulnerability is significant as it enables remote code execution capabilities for attackers who can successfully exploit the memory corruption. Once executed, the malicious code can run with the privileges of the user running the vulnerable Adobe Acrobat Reader application, potentially leading to full system compromise. The vulnerability affects users across multiple operating systems including windows platforms where Adobe Acrobat Reader is installed, making it a widespread concern for enterprise environments. Organizations relying on Adobe Reader for document viewing are particularly vulnerable, as the software is commonly used to open PDF documents that may contain embedded EMF graphics. The attack surface is broadened by the fact that these vulnerable versions are still in use across many organizations, creating persistent exposure windows.
Mitigation strategies should focus on immediate software updates to the latest versions of Adobe Acrobat Reader where the vulnerability has been patched. Organizations should implement strict document filtering policies to prevent opening of suspicious EMF files, particularly those that may contain private data structures. Network-based protections such as web application firewalls and email filtering solutions can help detect and block malicious documents before they reach end users. Security teams should also consider implementing application whitelisting policies that restrict execution of untrusted PDF files containing embedded graphics. Additionally, regular security awareness training should emphasize the risks of opening unknown or untrusted documents, as this vulnerability relies heavily on social engineering to achieve successful exploitation. The remediation process should include comprehensive vulnerability scanning to identify all systems running vulnerable versions of Adobe Reader, followed by systematic patch deployment across the enterprise environment.