CVE-2021-34309 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 write past the end of an allocated structure. An attacker could leverage this vulnerability to execute code in the context of the current process. (ZDI-CAN-13350)
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Analysis
by VulDB Data Team • 07/16/2021
This vulnerability exists within the tiff_loader.dll library component of JT2Go and Teamcenter Visualization software versions prior to V13.2, representing a critical security flaw that enables remote code execution through improper input validation. The vulnerability stems from insufficient bounds checking during TIFF file parsing operations, specifically when processing user-supplied data that is not adequately sanitized or validated before being processed by the application. The flaw manifests as an out-of-bounds write condition that occurs when the application attempts to write data beyond the allocated memory structure boundaries, creating a potential exploitation vector for malicious actors.
The technical implementation of this vulnerability involves the manipulation of TIFF file format structures where the tiff_loader.dll component fails to properly validate the size parameters and data offsets within the image file headers. When an attacker crafts a specially malformed TIFF file containing malicious data sequences, the library processes these inputs without adequate boundary checks, leading to memory corruption that can be exploited to overwrite adjacent memory locations. This type of vulnerability falls under the CWE-121 category of "Stack-based Buffer Overflow" and aligns with ATT&CK technique T1059.007 for command and scripting interpreter, as successful exploitation could enable arbitrary code execution with the privileges of the running process. The out-of-bounds write condition creates a predictable memory corruption pattern that attackers can leverage to inject and execute malicious code within the application context.
The operational impact of this vulnerability is severe as it allows remote code execution without requiring authentication, making it particularly dangerous in enterprise environments where these visualization tools are commonly used for design and engineering collaboration. An attacker could upload a malicious TIFF file through any means that allows file processing within the affected applications, potentially gaining full control over the system running the vulnerable software. The exploitation could lead to data breaches, system compromise, and lateral movement within network environments where these applications are deployed. Organizations using JT2Go and Teamcenter Visualization in manufacturing, engineering, or design workflows face significant risk, as these applications often process files from external sources or collaborative environments where untrusted input is common.
Mitigation strategies should prioritize immediate patching of all affected versions to V13.2 or later, as this represents the most effective defense against exploitation. Organizations should also implement network segmentation and file validation controls to prevent unauthorized TIFF file processing, particularly in environments where users may encounter untrusted content. Additional protective measures include restricting file upload capabilities, implementing strict input validation for all image file processing, and monitoring for unusual file processing patterns that could indicate exploitation attempts. Security teams should also consider deploying runtime application self-protection solutions that can detect and prevent memory corruption exploits, while maintaining regular vulnerability assessments to identify similar issues in other third-party components. The remediation process should include comprehensive testing of patched applications to ensure that the security fix does not introduce regressions in legitimate functionality.