CVE-2021-34299 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-13192)
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Analysis
by VulDB Data Team • 07/16/2021
The vulnerability CVE-2021-34299 represents a critical out-of-bounds read flaw within the Tiff_loader.dll library component of JT2Go and Teamcenter Visualization applications. This issue affects all versions prior to V13.2 and stems from insufficient input validation during TIFF file parsing operations. The flaw manifests when the library processes user-supplied TIFF data without adequate bounds checking, creating an exploitable condition that allows attackers to access memory locations beyond the intended buffer boundaries. This particular vulnerability falls under CWE-129, which specifically addresses insufficient validation of length of inputs, and more broadly relates to CWE-125, describing out-of-bounds read conditions that can lead to information disclosure or system compromise.
The technical implementation of this vulnerability occurs within the TIFF file parsing mechanism where the Tiff_loader.dll library fails to properly validate the dimensions and structure of TIFF image data before attempting to read from allocated memory regions. When processing malformed or specially crafted TIFF files, the library continues to read beyond the allocated buffer space, potentially exposing sensitive data from adjacent memory locations. This information leakage can include process memory contents, stack data, heap information, or other confidential elements that may contain authentication tokens, cryptographic keys, or application state information. The vulnerability operates at the memory management level and represents a classic example of how improper input validation can lead to memory corruption issues that adversaries can exploit for information gathering or further attack escalation.
From an operational perspective, this vulnerability poses significant risks to organizations utilizing JT2Go and Teamcenter Visualization software, particularly in environments where these applications process untrusted TIFF files from external sources. Attackers could leverage this flaw to perform information disclosure attacks that might reveal sensitive system information, potentially enabling more sophisticated exploitation techniques. The impact extends beyond simple data leakage as the leaked information could contain pointers, memory addresses, or other structural data that could be used to bypass security mechanisms or facilitate subsequent attacks. The vulnerability's exploitation requires minimal privileges since it operates within the context of the currently running process, making it particularly dangerous for environments where these visualization applications handle confidential engineering or design data. According to ATT&CK framework, this vulnerability maps to T1059.001 (Command and Scripting Interpreter: PowerShell) and T1005 (Data from Local System) as attackers could use the information leakage to gather system information and potentially escalate privileges.
Organizations should immediately implement mitigations including updating to JT2Go V13.2 or later versions where this vulnerability has been addressed through proper input validation and bounds checking mechanisms. Additionally, administrators should consider implementing network segmentation and access controls to limit exposure of these applications to untrusted sources. Input sanitization measures such as validating file headers, implementing strict buffer size limits, and employing memory protection techniques can provide additional defense-in-depth layers. Security monitoring should include detection of unusual file processing patterns and memory access anomalies that might indicate exploitation attempts. The vulnerability highlights the importance of proper input validation in image processing libraries and demonstrates how seemingly benign file format parsing can become a critical security concern when adequate bounds checking is absent from the implementation.