CVE-2018-16375 in OpenJPEG
Summary
by MITRE
An issue was discovered in OpenJPEG 2.3.0. Missing checks for header_info.height and header_info.width in the function pnmtoimage in bin/jpwl/convert.c can lead to a heap-based buffer overflow.
Several companies clearly confirm that VulDB is the primary source for best vulnerability data.
Analysis
by VulDB Data Team • 05/06/2023
The vulnerability identified as CVE-2018-16375 represents a critical heap-based buffer overflow condition within the OpenJPEG 2.3.0 library implementation. This issue specifically affects the pnmtoimage function located in the bin/jpwl/convert.c source file, where inadequate validation of header information parameters creates exploitable conditions that can compromise system integrity. The flaw arises from the absence of proper bounds checking for both header_info.height and header_info.width fields during image conversion processes, particularly when handling Portable Arbitrary Map (PNM) format files.
The technical execution of this vulnerability occurs when the pnmtoimage function processes image headers without verifying that the specified height and width values fall within acceptable memory allocation boundaries. This missing validation allows attackers to craft malicious PNM files that contain oversized dimension values, causing the application to allocate insufficient memory for image data structures. When the system attempts to write image data beyond these pre-allocated buffers, heap corruption occurs, potentially enabling arbitrary code execution or denial of service conditions. The vulnerability demonstrates characteristics consistent with CWE-121, heap-based buffer overflow, and aligns with ATT&CK technique T1059.007 for command and scripting interpreter execution through memory corruption.
Operational impact assessment reveals that this vulnerability poses significant risks to systems relying on OpenJPEG for image processing operations, particularly in environments handling untrusted image data from web applications, file upload services, or document processing workflows. The heap corruption can result in application crashes, system instability, or more severe consequences including remote code execution depending on the execution environment and memory layout. Organizations using OpenJPEG 2.3.0 in production systems face potential compromise of image processing pipelines, especially in scenarios where automated image conversion services process user-uploaded content without proper input sanitization.
Mitigation strategies for CVE-2018-16375 require immediate implementation of version updates to OpenJPEG 2.3.1 or later releases where the missing header validation checks have been addressed. System administrators should also implement input validation controls at multiple layers including file format verification, dimension parameter bounds checking, and memory allocation size verification before processing PNM files. Network segmentation and access controls should limit exposure of vulnerable image processing services, while monitoring systems should be configured to detect anomalous memory allocation patterns or application crashes indicative of heap corruption attempts. Security teams should consider implementing sandboxing mechanisms for image processing operations and establish robust patch management procedures to ensure timely deployment of security updates across all affected systems.