CVE-2021-45907 in gif2apng
Summary
by MITRE • 12/28/2021
An issue was discovered in gif2apng 1.9. There is a stack-based buffer overflow involving a for loop. An attacker has little influence over the data written to the stack, making it unlikely that the flow of control can be subverted.
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Analysis
by VulDB Data Team • 12/31/2021
The vulnerability identified as CVE-2021-45907 represents a stack-based buffer overflow in the gif2apng utility version 1.9, a tool designed to convert gif image files to apng format. This flaw resides within the software's handling of image data during the conversion process, specifically manifesting in a for loop structure that fails to properly validate input boundaries. The gif2apng utility operates as a command-line tool for image format conversion, making it susceptible to exploitation in environments where users might process untrusted gif files from external sources. The vulnerability stems from inadequate bounds checking mechanisms that allow excessive data to be written beyond the allocated stack buffer space, creating potential memory corruption conditions that could be leveraged by malicious actors.
The technical nature of this buffer overflow presents specific characteristics that influence its exploitability and impact potential. The flaw occurs during the processing of gif image data where a for loop iterates through image frames or pixel data without sufficient boundary validation. While the attacker's influence over data written to the stack is described as limited, the vulnerability still represents a significant security risk due to the potential for memory corruption that could lead to arbitrary code execution under certain conditions. The stack-based nature of the overflow means that the corruption affects the program's execution stack, potentially allowing attackers to overwrite return addresses, saved registers, or other critical stack data structures. This type of vulnerability falls under the CWE-121 stack-based buffer overflow category, which is classified as a critical security weakness in software development practices.
The operational impact of CVE-2021-45907 extends beyond simple memory corruption, as it affects the integrity and stability of systems that utilize gif2apng for image processing tasks. In environments where automated processing of user-uploaded content occurs, or where the utility is invoked through web applications or service interfaces, this vulnerability could enable attackers to cause application crashes, data corruption, or potentially achieve remote code execution. The limited influence over data written to the stack suggests that direct control flow hijacking might be challenging, but the vulnerability still represents a valid attack surface that could be combined with other techniques or used in conjunction with information leakage vulnerabilities. The impact is particularly concerning in server environments where gif2apng might be used as part of content processing pipelines, as it could allow attackers to disrupt services or gain unauthorized access to system resources.
Mitigation strategies for CVE-2021-45907 should focus on both immediate remediation and long-term code quality improvements. The primary solution involves updating to a patched version of gif2apng that addresses the buffer overflow through proper bounds checking and input validation mechanisms. Organizations should also implement defensive programming practices such as stack canaries, address space layout randomization, and non-executable stack protections to reduce the exploitability of similar vulnerabilities. The vulnerability demonstrates the importance of input validation and boundary checking in image processing libraries, aligning with ATT&CK technique T1203 for exploitation of input validation flaws. Additionally, system administrators should consider implementing sandboxing mechanisms for image processing utilities, restricting their capabilities through privilege separation, and monitoring for unusual processing patterns that might indicate exploitation attempts. Regular security audits of image processing pipelines and input validation routines should be conducted to identify and remediate similar vulnerabilities before they can be exploited in real-world scenarios.