CVE-2018-17229 in Exiv2
Summary
by MITRE
Exiv2::d2Data in types.cpp in Exiv2 v0.26 allows remote attackers to cause a denial of service (heap-based buffer overflow) via a crafted image file.
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Analysis
by VulDB Data Team • 05/17/2023
The vulnerability identified as CVE-2018-17229 represents a critical heap-based buffer overflow flaw within the Exiv2 image processing library version 0.26. This issue resides in the Exiv2::d2Data function located in the types.cpp source file, which processes image metadata and handles various image formats including jpeg tiff and png. The flaw manifests when the library encounters specially crafted image files that contain malformed metadata structures, leading to improper memory allocation and subsequent buffer overflow conditions. The vulnerability is particularly concerning because it enables remote attackers to exploit the library through crafted image files without requiring any special privileges or user interaction, making it a significant threat in web applications and services that process user-uploaded images.
The technical implementation of this vulnerability stems from inadequate input validation and memory management within the Exiv2 library's metadata parsing routines. When the Exiv2::d2Data function processes image data, it fails to properly validate the size parameters of embedded metadata structures, particularly in the context of image headers and exif data. This allows attackers to craft image files containing oversized or malformed metadata fields that exceed the allocated buffer boundaries during processing. The heap-based nature of the overflow means that memory corruption occurs in the heap memory space rather than on the stack, potentially leading to more complex exploitation scenarios including arbitrary code execution or complete system compromise. The vulnerability is classified as a CWE-121 heap-based buffer overflow which is a well-documented class of memory safety issues that have been the subject of numerous security advisories and exploitation techniques.
The operational impact of CVE-2018-17229 extends beyond simple denial of service scenarios to encompass potential system compromise and service disruption across numerous applications that depend on Exiv2 for image processing. Web applications file servers content management systems and image processing platforms that utilize Exiv2 for metadata extraction and image validation become vulnerable to remote exploitation when processing untrusted image uploads. Attackers can leverage this vulnerability to crash applications causing denial of service conditions or potentially execute malicious code if the overflow leads to memory corruption that can be exploited through return-oriented programming or other advanced exploitation techniques. The vulnerability affects any system where Exiv2 v0.26 is installed and actively processing image files, including but not limited to web servers mobile applications and desktop software that handles image metadata processing.
Mitigation strategies for CVE-2018-17229 primarily involve immediate software updates to Exiv2 version 0.27 or later where the vulnerability has been addressed through proper input validation and memory boundary checks. Organizations should implement comprehensive patch management procedures to ensure all systems utilizing Exiv2 are updated promptly, particularly in environments where user-uploaded content is processed. Additional defensive measures include implementing strict input validation for image files before processing, utilizing sandboxed environments for image analysis, and deploying intrusion detection systems to monitor for exploitation attempts. The vulnerability aligns with ATT&CK technique T1203 (Exploitation for Client Execution) and T1059 (Command and Scripting Interpreter) as attackers may leverage such vulnerabilities to establish persistent access or escalate privileges within compromised systems. Security monitoring should focus on identifying unusual memory allocation patterns and process crashes that may indicate exploitation attempts, while network segmentation can help limit the impact of successful attacks by isolating vulnerable applications from critical system resources.