CVE-2017-7939 in ImageWorsener
Summary
by MITRE
The read_next_pam_token function in imagew-pnm.c in libimageworsener.a in ImageWorsener 1.3.0 allows remote attackers to cause a denial of service (stack-based buffer over-read) via a crafted file.
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Analysis
by VulDB Data Team • 11/29/2022
The vulnerability identified as CVE-2017-7939 represents a critical stack-based buffer over-read flaw within the ImageWorsener image processing library version 1.3.0. This issue specifically affects the read_next_pam_token function located in the imagew-pnm.c source file of the libimageworsener.a library. The flaw arises when the library processes specially crafted image files that exploit improper bounds checking during token reading operations. Attackers can leverage this vulnerability by submitting maliciously formatted files to systems that utilize ImageWorsener for image processing, potentially leading to system instability and denial of service conditions. The vulnerability demonstrates a classic stack buffer over-read condition where the application attempts to read memory beyond the allocated buffer boundaries, creating an exploitable scenario that can be remotely triggered.
The technical implementation of this vulnerability stems from inadequate input validation and memory management within the PNM (Portable AnyMap) file format parser. When the read_next_pam_token function processes image data, it fails to properly verify the size of incoming data segments against the allocated buffer space. This allows an attacker to craft PNM files with malformed token sequences that cause the function to read beyond its intended memory boundaries. The flaw operates at the application level within the image processing pipeline, making it particularly dangerous as it can be exploited through standard file upload mechanisms or image processing workflows. The vulnerability is classified under CWE-121 as a stack-based buffer overflow, though the specific nature of the over-read indicates a more precise manifestation of memory corruption issues.
Operationally, this vulnerability creates significant risk for systems that rely on ImageWorsener for image handling, particularly web applications, content management systems, and digital asset management platforms. The remote exploitation capability means that attackers can trigger denial of service conditions without requiring local system access or authentication. Systems processing user-uploaded images become prime targets for this attack vector, as the malicious file can be delivered through normal upload workflows. The impact extends beyond simple service disruption to potentially enable more sophisticated attacks if combined with other vulnerabilities, as the memory corruption could provide opportunities for code execution or information disclosure. Organizations using this library in production environments face immediate risk of service interruption and potential compromise of their image processing pipelines.
Mitigation strategies for CVE-2017-7939 should prioritize immediate patching of the ImageWorsener library to version 1.3.1 or later, which contains the necessary fixes for the buffer over-read condition. Organizations should implement input validation measures that sanitize all image files before processing, including size limits and format verification. Network-based defenses such as web application firewalls can be configured to detect and block suspicious image file patterns that may indicate exploitation attempts. Additionally, system administrators should consider implementing sandboxing mechanisms for image processing operations to isolate potential memory corruption effects. The vulnerability aligns with ATT&CK technique T1203 - Exploitation for Client Execution, as it represents a remote code execution vector through file processing. Regular security assessments and vulnerability scanning should be conducted to identify systems still running vulnerable versions of ImageWorsener, while incident response procedures should be updated to address potential exploitation attempts targeting this specific flaw.