CVE-2017-14232 in Free Lossless Image Format
Summary
by MITRE
The read_chunk function in flif-dec.cpp in Free Lossless Image Format (FLIF) 0.3 allows remote attackers to cause a denial of service (invalid memory read and application crash) via a crafted flif file.
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Analysis
by VulDB Data Team • 07/29/2020
The vulnerability identified as CVE-2017-14232 resides within the Free Lossless Image Format (FLIF) decoder implementation, specifically in the read_chunk function located in the flif-dec.cpp source file. This issue affects FLIF version 0.3 and represents a critical denial of service vulnerability that can be exploited by remote attackers through the careful crafting of malicious FLIF image files. The flaw manifests when the decoder processes malformed input data, leading to invalid memory read operations that ultimately result in application crashes and system instability. This vulnerability directly impacts the robustness and reliability of any system that processes FLIF image files, particularly those deployed in environments where user-supplied content is accepted without proper validation.
The technical root cause of this vulnerability stems from inadequate input validation and memory management within the read_chunk function. When processing a specially crafted FLIF file, the function fails to properly validate the boundaries and integrity of the chunk data structures, allowing attackers to manipulate the decoder's memory access patterns. This flaw enables attackers to trigger invalid memory reads that cause the application to access memory locations that are either unmapped or protected, leading to segmentation faults and subsequent application termination. The vulnerability demonstrates characteristics consistent with CWE-125: Out-of-bounds Read, where the application reads memory beyond the intended buffer boundaries, and CWE-476: NULL Pointer Dereference, when the decoder attempts to access memory through invalid pointers. The attack vector operates through the standard file processing workflow, making it particularly dangerous as it can be triggered simply by opening or processing a malicious FLIF file.
The operational impact of this vulnerability extends beyond simple service disruption, as it can be leveraged in various attack scenarios that compromise system availability and stability. In web applications or content management systems that accept FLIF uploads, attackers can upload malicious files that will cause the image processing pipeline to crash whenever the files are accessed or converted. This creates a persistent denial of service condition that can be exploited to disrupt legitimate service operations, particularly in environments where automated image processing is performed. The vulnerability also poses risks in networked environments where FLIF files are processed through automated systems, as it can be used to cause cascading failures when multiple processes are simultaneously affected. From an attacker perspective, this vulnerability aligns with ATT&CK technique T1499.004: Endpoint Denial of Service, which specifically targets the exhaustion of system resources or the corruption of application state through manipulation of input data.
Mitigation strategies for CVE-2017-14232 should focus on immediate patching of affected systems, as the vulnerability is fully remediable through code updates that implement proper input validation and memory boundary checking. System administrators should ensure that all FLIF processing components are updated to versions that contain the necessary security fixes, which typically involve implementing bounds checking mechanisms and proper error handling for chunk data processing. Additionally, defensive measures should include input sanitization and validation at multiple layers, particularly when processing user-supplied FLIF files. Organizations should consider implementing sandboxing techniques for image processing operations to limit the potential impact of any remaining vulnerabilities. Network-based mitigations can include content filtering systems that identify and block suspicious FLIF file patterns, while application-level protections should enforce strict memory access controls and implement robust error handling that prevents invalid memory operations from causing application crashes. The vulnerability also underscores the importance of comprehensive input validation and the need for thorough security testing of image processing libraries to prevent similar issues in other multimedia formats.