CVE-2019-14288 in Xpdf
Summary
by MITRE
An issue was discovered in Xpdf 4.01.01. There is an Integer overflow in the function JBIG2Bitmap::combine at JBIG2Stream.cc for the "one byte per line" case.
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Analysis
by VulDB Data Team • 11/13/2023
The vulnerability identified as CVE-2019-14288 represents a critical integer overflow flaw within the Xpdf 4.01.01 document processing library, specifically affecting the JBIG2Bitmap::combine function in the JBIG2Stream.cc source file. This issue arises during processing of JBIG2 compressed image data, which is commonly used in document formats such as PDF files for fax and image compression. The vulnerability manifests when handling the "one byte per line" case, indicating that the flaw is specifically triggered under certain memory allocation patterns typical of JBIG2 image processing workflows. The integer overflow occurs during arithmetic operations that should theoretically remain within safe bounds, but due to improper boundary checking, the calculation results in an unexpectedly large value that can cause memory corruption or unpredictable behavior in the application.
The technical nature of this vulnerability places it squarely within the CWE-190 category of Integer Overflow or Wraparound, which is a fundamental class of software defects that has been consistently ranked among the top security vulnerabilities in industry assessments. The flaw demonstrates poor input validation and inadequate overflow checking mechanisms in the memory allocation calculations used by the JBIG2 decoding engine. When the integer overflow occurs, it can lead to insufficient memory allocation for the bitmap data structure, creating potential for buffer overflows, memory corruption, or arbitrary code execution depending on how the corrupted memory is subsequently accessed. This type of vulnerability is particularly dangerous in document processing applications because it can be triggered through seemingly benign document content, making it an ideal candidate for remote code execution attacks when the vulnerable library is used in web applications or document viewers.
The operational impact of CVE-2019-14288 extends beyond simple memory corruption, as it can enable attackers to manipulate the execution flow of applications that utilize the Xpdf library for PDF processing. The vulnerability affects systems that process JBIG2 compressed images, which are prevalent in PDF documents, particularly those generated by fax machines, government documents, or scientific publications. Attackers could potentially craft malicious PDF files containing specially constructed JBIG2 data that triggers the integer overflow during document rendering, leading to potential privilege escalation or complete system compromise. This vulnerability aligns with ATT&CK technique T1203 by enabling adversaries to gain access to system resources through software exploitation, and it represents a classic example of how memory safety issues in widely used libraries can create widespread security implications across numerous applications and platforms.
Mitigation strategies for CVE-2019-14288 must focus on immediate patching of the Xpdf library to version 4.01.02 or later, which contains the necessary fixes for the integer overflow condition. System administrators should also implement defensive measures such as restricting document processing capabilities for untrusted content, employing sandboxing techniques for PDF rendering operations, and monitoring for unusual memory allocation patterns that might indicate exploitation attempts. Additionally, organizations using Xpdf in their applications should conduct thorough code reviews to identify similar integer overflow vulnerabilities in other parts of their software stack, particularly in areas involving image processing or memory allocation calculations. The vulnerability demonstrates the critical importance of proper integer overflow checking in security-critical code, especially in libraries that process untrusted data from external sources, and reinforces the need for comprehensive security testing including fuzzing and formal verification techniques to identify similar issues before they can be exploited in the wild.