CVE-2018-4884 in Acrobat Reader
Summary
by MITRE
An issue was discovered in Adobe Acrobat Reader 2018.009.20050 and earlier versions, 2017.011.30070 and earlier versions, 2015.006.30394 and earlier versions. This vulnerability occurs as a result of computation that reads data that is past the end of the target buffer; the computation is part of the image conversion engine when processing Enhanced Metafile Format (EMF) data that embeds an image in the bitmap (BMP) file format. A successful attack can lead to sensitive data exposure.
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Analysis
by VulDB Data Team • 07/23/2024
This vulnerability exists within Adobe Acrobat Reader's image conversion engine and represents a classic buffer overflow condition that occurs during processing of Enhanced Metafile Format files containing embedded bitmap data. The flaw manifests when the application attempts to read beyond the boundaries of a targeted buffer during EMF file processing, specifically when handling BMP format image data embedded within EMF containers. This type of vulnerability falls under the category of buffer over-read conditions that are classified as CWE-125 in the Common Weakness Enumeration catalog. The vulnerability affects multiple versions of Adobe Acrobat Reader spanning from 2015 through 2018, indicating a prolonged period of exposure within the software's codebase.
The technical execution of this vulnerability requires an attacker to craft a malicious EMF file that contains specifically formatted embedded BMP data which triggers the buffer over-read condition during image conversion processing. When the application processes such a file, the image conversion engine performs computations that access memory locations beyond the allocated buffer boundaries, potentially exposing sensitive information stored in adjacent memory regions. This memory access pattern can lead to information disclosure vulnerabilities where attackers might extract confidential data, session tokens, or other sensitive information from the application's memory space. The vulnerability's impact is particularly concerning because it operates at the file parsing level where user interaction is required to trigger the malicious code path.
From an operational perspective, this vulnerability creates a significant risk for organizations relying on Adobe Acrobat Reader for document processing, as it can be exploited through social engineering attacks involving malicious document attachments. The attack vector typically involves luring users to open specially crafted EMF files that contain embedded BMP data, which then triggers the buffer over-read condition when the application attempts to render or process the embedded image. This vulnerability aligns with ATT&CK technique T1204.002 for legitimate user execution, where adversaries leverage the trust users place in document readers to execute malicious code. The exposure of sensitive data through this mechanism can compromise user privacy, organizational security, and potentially lead to further exploitation opportunities.
Organizations should prioritize immediate remediation by updating to patched versions of Adobe Acrobat Reader, as Adobe released security updates addressing this specific vulnerability. System administrators should implement application whitelisting policies to restrict execution of untrusted EMF files and consider deploying sandboxing solutions to isolate document processing activities. Network-based detection measures can be implemented to identify suspicious EMF file patterns, and regular security assessments should be conducted to ensure proper patch management. The vulnerability demonstrates the importance of thorough input validation and proper buffer boundary checking in multimedia processing libraries, highlighting the need for comprehensive security testing of file format parsers and image conversion engines. Organizations should also consider implementing email filtering solutions that can identify and block suspicious document attachments that may contain malicious EMF files designed to exploit this and similar buffer over-read vulnerabilities.