CVE-2016-8691 in Jasper
Summary
by MITRE
The jpc_dec_process_siz function in libjasper/jpc/jpc_dec.c in JasPer before 1.900.4 allows remote attackers to cause a denial of service (divide-by-zero error and application crash) via a crafted XRsiz value in a BMP image to the imginfo command.
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Analysis
by VulDB Data Team • 08/15/2020
The vulnerability identified as CVE-2016-8691 represents a critical denial of service flaw within the JasPer image processing library, specifically affecting versions prior to 1.900.4. This issue resides in the jpc_dec_process_siz function located within the libjasper/jpc/jpc_dec.c source file, demonstrating how seemingly innocuous image metadata can be exploited to compromise system stability. The vulnerability manifests when the imginfo command processes BMP images containing maliciously crafted XRsiz values, creating a scenario where remote attackers can intentionally trigger system failures without requiring authentication or privileged access. The flaw operates through a divide-by-zero error condition that fundamentally disrupts the normal execution flow of the image processing pipeline, leading to application crashes that can be leveraged for denial of service attacks against systems relying on JasPer for image handling operations.
The technical implementation of this vulnerability stems from inadequate input validation within the JPEG 2000 decoder component of JasPer, which fails to properly sanitize the XRsiz parameter during image header parsing. When the imginfo utility encounters a BMP image with an invalid XRsiz value, the jpc_dec_process_siz function attempts to perform division operations using this malformed parameter, resulting in a mathematical exception that terminates the application process. This type of vulnerability aligns with CWE-369, which categorizes divide-by-zero errors as a fundamental flaw in input validation and error handling mechanisms. The vulnerability is particularly concerning because it operates at the decoding level of image processing, where applications often process untrusted input from external sources, making it a prime target for exploitation in web applications, file processing services, and image conversion utilities that depend on JasPer for format support.
The operational impact of CVE-2016-8691 extends beyond simple application crashes to potentially disrupt entire service availability, especially in environments where image processing is a core function. Systems utilizing JasPer for image handling, including web servers, content management systems, and digital asset management platforms, become vulnerable to sustained denial of service attacks that can render image processing capabilities completely inoperable. Attackers can exploit this vulnerability through various vectors including email attachments, file upload interfaces, or web-based image processing services, making it particularly dangerous in multi-tenant environments where a single malicious image could affect multiple users or processes. The vulnerability's remote exploitability means that attackers do not require physical access to the target system, allowing for widespread impact across networks and cloud environments that utilize JasPer-based image processing workflows.
Mitigation strategies for CVE-2016-8691 focus primarily on upgrading to JasPer version 1.900.4 or later, which incorporates proper input validation and error handling to prevent the divide-by-zero condition. Organizations should implement comprehensive patch management processes to ensure all systems utilizing JasPer are updated promptly, particularly those handling untrusted image input from external sources. Additional defensive measures include implementing input sanitization layers that validate image parameters before processing, deploying network segmentation to isolate image processing services, and establishing monitoring protocols to detect unusual application behavior that may indicate exploitation attempts. From an operational security perspective, this vulnerability highlights the importance of maintaining up-to-date third-party libraries and implementing robust input validation across all image processing pipelines, as specified in the ATT&CK framework's defense evasion and privilege escalation techniques. The vulnerability serves as a reminder of the critical need for proper error handling in cryptographic and image processing libraries, where mathematical operations must always account for edge cases and invalid input conditions to prevent system instability and potential exploitation by malicious actors.