CVE-2021-34303 in JT2Go
Summary
by MITRE • 07/13/2021
A vulnerability has been identified in JT2Go (All versions < V13.2), Teamcenter Visualization (All versions < V13.2). The Tiff_Loader.dll library in affected applications lacks proper validation of user-supplied data when parsing TIFF files. This could result in an out of bounds read past the end of an allocated buffer. An attacker could leverage this vulnerability to leak information in the context of the current process. (ZDI-CAN-13198)
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Analysis
by VulDB Data Team • 07/16/2021
The vulnerability identified as CVE-2021-34303 resides within the Tiff_Loader.dll library component of JT2Go and Teamcenter Visualization applications, affecting all versions prior to V13.2. This flaw represents a critical security weakness that stems from inadequate input validation during TIFF file processing operations. The affected software components are widely used in engineering and product visualization environments where users frequently handle various file formats including TIFF images. The vulnerability specifically manifests when the application attempts to parse TIFF files without sufficient boundary checking mechanisms, creating a scenario where maliciously crafted input can trigger unexpected behavior.
The technical implementation of this vulnerability falls under the category of out-of-bounds read conditions as classified by CWE-125, where the Tiff_Loader.dll library fails to properly validate buffer boundaries during TIFF file parsing operations. When a TIFF file is processed, the library allocates memory buffers to store image data but does not adequately verify that subsequent read operations remain within the allocated memory boundaries. This allows an attacker to craft a specially formatted TIFF file that, when opened by the vulnerable application, causes the parser to read beyond the intended buffer limits. The consequence of this improper validation is that the application may access memory locations containing sensitive information from the process heap, potentially exposing system memory contents including credentials, temporary data, or other confidential information.
From an operational perspective, this vulnerability presents significant risks to organizations relying on JT2Go and Teamcenter Visualization for their product development and visualization workflows. The attack vector requires an attacker to convince a legitimate user to open a malicious TIFF file, which typically occurs through social engineering tactics such as email attachments or compromised file sharing platforms. The impact extends beyond simple information disclosure as the leaked memory contents could contain sensitive data that might aid in further exploitation attempts or provide attackers with insights into system memory layout and application behavior. This vulnerability aligns with ATT&CK technique T1059.007 for execution through scripting and T1566 for initial access through social engineering, making it particularly dangerous in enterprise environments where these visualization tools are commonly used.
Organizations should immediately implement mitigations including updating to the patched versions V13.2 or later of both JT2Go and Teamcenter Visualization applications. The vendor has addressed this issue through proper input validation mechanisms that ensure all buffer operations remain within allocated memory boundaries during TIFF file processing. Additionally, administrators should consider implementing restrictive file access policies that limit the types of files users can open within these applications, particularly in environments where untrusted file sources exist. Network-based mitigations such as content filtering and email scanning can help prevent the delivery of malicious TIFF files to end users. The vulnerability also highlights the importance of input validation in all file parsing components and aligns with security best practices outlined in NIST SP 800-160 and ISO/IEC 27001 standards for secure software development practices. Organizations should conduct thorough vulnerability assessments to identify any other applications using similar TIFF parsing libraries and ensure comprehensive patch management across their software ecosystem.