CVE-2025-47758 in V-SFT
Summary
by MITRE • 05/19/2025
V-SFT v6.2.5.0 and earlier contains an issue with stack-based buffer overflow in VS6File!CTxSubFile::get_ProgramFile_name function. Opening specially crafted V7 or V8 files may lead to crash, information disclosure, and arbitrary code execution.
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
Analysis
by VulDB Data Team • 05/19/2025
The vulnerability identified as CVE-2025-47758 affects V-SFT version 6.2.5.0 and earlier implementations, specifically within the VS6File!CTxSubFile::get_ProgramFile_name function. This represents a critical stack-based buffer overflow condition that emerges when processing specially crafted V7 or V8 file formats. The flaw resides in the software's file parsing mechanism where insufficient bounds checking occurs during the extraction and handling of program file names from these proprietary file structures. Such buffer overflow conditions are particularly dangerous as they can be exploited to overwrite adjacent memory locations on the stack, potentially leading to complete system compromise.
The technical exploitation of this vulnerability occurs through the manipulation of input data within V7 or V8 file formats that are processed by the vulnerable software. When the CTxSubFile::get_ProgramFile_name function attempts to parse malformed file data, it fails to validate the length of string data being copied into fixed-size stack buffers. This allows an attacker to supply input data that exceeds the allocated buffer space, causing a stack overflow condition. The vulnerability is classified as a classic stack-based buffer overflow which aligns with CWE-121, representing a weakness where insufficient bounds checking allows a buffer to be overwritten. Attackers can leverage this condition to execute arbitrary code with the privileges of the affected application, potentially leading to complete system compromise.
The operational impact of this vulnerability extends beyond simple application crashes to encompass serious security implications including information disclosure and arbitrary code execution capabilities. When exploited, the buffer overflow can lead to denial of service conditions through application crashes, but more critically can enable attackers to execute malicious code within the context of the vulnerable application. The vulnerability affects systems running V-SFT versions up to and including 6.2.5.0, making it particularly concerning for organizations that have not yet updated their software installations. The potential for information disclosure means that sensitive data stored in memory could be accessed by unauthorized parties, while the arbitrary code execution capability provides a complete attack surface for further exploitation. According to ATT&CK framework, this vulnerability maps to T1059.007 for command and scripting interpreter and T1566 for credential access through file and information manipulation.
Mitigation strategies for CVE-2025-47758 should prioritize immediate software updates to versions that have addressed this buffer overflow condition. Organizations should implement network segmentation and access controls to limit exposure of vulnerable systems to untrusted file inputs. Input validation measures should be strengthened at all levels of the application stack to prevent malformed data from reaching the vulnerable parsing functions. System administrators should consider implementing application whitelisting policies to restrict execution of untrusted file formats. Additionally, monitoring systems should be configured to detect unusual file processing patterns or potential exploitation attempts. The vulnerability demonstrates the importance of proper bounds checking in memory management and highlights the need for regular security assessments of file processing functions. Organizations should also consider deploying intrusion detection systems that can identify exploitation attempts targeting stack-based buffer overflow conditions, as these attacks often follow predictable patterns that can be detected through behavioral analysis.