CVE-2018-5268 in OpenCV
Summary
by MITRE
In OpenCV 3.3.1, a heap-based buffer overflow happens in cv::Jpeg2KDecoder::readComponent8u in modules/imgcodecs/src/grfmt_jpeg2000.cpp when parsing a crafted image file.
If you want to get best quality of vulnerability data, you may have to visit VulDB.
Analysis
by VulDB Data Team • 01/20/2023
The vulnerability CVE-2018-5268 represents a critical heap-based buffer overflow within the OpenCV library version 3.3.1, specifically within the JPEG 2000 image decoding module. This flaw exists in the cv::Jpeg2KDecoder::readComponent8u function located in modules/imgcodecs/src/grfmt_jpeg2000.cpp, making it a direct result of improper input validation during image file parsing operations. The vulnerability manifests when processing maliciously crafted JPEG 2000 image files that contain malformed data structures, particularly within the component data sections of the format. This issue falls under CWE-121 Heap-based Buffer Overflow, which is classified as a memory safety error where data written to heap memory exceeds the allocated buffer boundaries, potentially leading to memory corruption and arbitrary code execution. The vulnerability is particularly concerning because OpenCV is widely used across various applications including security tools, medical imaging systems, and computer vision platforms, making it a prime target for exploitation in remote code execution scenarios. Attackers can leverage this vulnerability by crafting specially designed JPEG 2000 files that, when processed by vulnerable applications, trigger the buffer overflow condition.
The technical implementation of this vulnerability stems from insufficient bounds checking during the parsing of JPEG 2000 component data structures. When the readComponent8u function processes image components, it fails to adequately validate the size parameters extracted from the malformed input file, leading to a situation where the program attempts to write data beyond the allocated memory buffer. This memory corruption occurs in the heap memory region, making exploitation more complex but still feasible through carefully constructed attack vectors. The flaw is particularly dangerous because JPEG 2000 is a widely supported image format used in professional and medical applications, meaning that a successful exploitation could impact critical infrastructure systems. The vulnerability exists in the image processing pipeline where the application receives user-provided image files and processes them without adequate sanitization of the input data. The attack surface is broad since any application that utilizes OpenCV's image handling capabilities and processes JPEG 2000 files could be affected, including content management systems, image viewers, and security applications that rely on OpenCV for image analysis.
The operational impact of CVE-2018-5268 extends beyond simple denial of service scenarios, as it presents a significant risk for remote code execution attacks that could compromise entire systems. When exploited, this vulnerability allows attackers to overwrite adjacent memory locations, potentially leading to stack corruption, heap corruption, or even arbitrary code execution depending on the target environment and memory layout. The vulnerability is particularly dangerous in web applications where users can upload image files, as it could enable attackers to execute malicious code on servers processing these images. The exploitability of this vulnerability is enhanced by the fact that JPEG 2000 is a legitimate image format that many applications expect to handle, making it difficult for security systems to distinguish between normal and malicious file processing. Organizations using OpenCV in security-sensitive applications face particular risk, as this vulnerability could be leveraged to bypass security controls in systems designed to process and analyze image data for threat detection and response. The vulnerability's impact is amplified by the widespread adoption of OpenCV in both commercial and open-source projects, meaning that a single exploitation could affect numerous applications across different industries.
Mitigation strategies for CVE-2018-5268 primarily involve immediate patching of OpenCV installations to version 3.4.1 or later, which contains the necessary fixes for the buffer overflow vulnerability. Organizations should conduct comprehensive vulnerability assessments to identify all systems and applications that utilize vulnerable versions of OpenCV, particularly those that process user-provided image files. Input validation and sanitization measures should be implemented at the application level to filter out potentially malicious image files before they reach the OpenCV processing functions. Network-based security controls including intrusion prevention systems and web application firewalls should be configured to detect and block suspicious image file uploads that may contain crafted JPEG 2000 data structures. Additionally, organizations should consider implementing sandboxing techniques for image processing operations to limit the potential impact of successful exploitation attempts. The remediation process should include thorough testing of patched versions to ensure that legitimate image processing functionality remains intact while the vulnerability is addressed. Security monitoring should be enhanced to detect unusual patterns in image processing activities that might indicate exploitation attempts. System administrators should also review and update their incident response procedures to include specific protocols for handling buffer overflow vulnerabilities in image processing libraries, ensuring rapid response capabilities when such threats are detected in production environments.