CVE-2020-37181 in Torrent FLV Converter
Summary
by MITRE • 02/11/2026
Torrent FLV Converter 1.51 Build 117 contains a stack overflow vulnerability that allows attackers to overwrite Structured Exception Handler (SEH) through a malicious registration code input. Attackers can craft a payload with specific offsets and partial SEH overwrite techniques to potentially execute arbitrary code on vulnerable Windows 32-bit systems.
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Analysis
by VulDB Data Team • 02/11/2026
The vulnerability identified as CVE-2020-37181 resides within Torrent FLV Converter version 1.51 Build 117, a multimedia conversion tool that processes video files into flv format. This particular software implementation suffers from a critical stack overflow condition that manifests when processing user-supplied registration code inputs. The flaw represents a classic buffer overflow vulnerability that occurs within the application's input validation mechanisms, specifically when handling structured exception handler data structures. The vulnerability is particularly concerning as it affects 32-bit Windows systems and provides attackers with a pathway to execute arbitrary code through controlled manipulation of the application's exception handling routines.
The technical exploitation of this vulnerability leverages the Structured Exception Handler (SEH) overwrite technique, which targets the exception handling mechanism that Windows uses to manage program crashes and errors. When the application processes a malicious registration code, the insufficient bounds checking allows an attacker to overflow the stack buffer and overwrite the SEH frame pointer. This overwrite enables the attacker to redirect program execution flow by placing malicious code pointers within the SEH chain, effectively allowing code execution in the context of the vulnerable application process. The vulnerability classifies under CWE-121 as a stack-based buffer overflow, where insufficient bounds checking allows an attacker to write past the end of a stack buffer and overwrite adjacent memory locations including exception handlers.
The operational impact of this vulnerability extends beyond simple code execution, as it provides attackers with a potential foothold for more sophisticated attacks within the target environment. An attacker who successfully exploits this vulnerability can gain arbitrary code execution with the privileges of the user running the Torrent FLV Converter application, which typically runs with standard user privileges. The attack requires minimal user interaction, as the vulnerability is triggered through the registration code input field, making it particularly dangerous in scenarios where users might be tricked into entering malicious registration codes. This vulnerability aligns with ATT&CK technique T1059.007 for command and scripting interpreter, as successful exploitation would enable attackers to execute commands through the compromised application, and T1203 for exploitation for privilege escalation.
Mitigation strategies for CVE-2020-37181 should prioritize immediate software updates from the vendor, as the vulnerability affects a specific version of the application that likely contains a patched version. System administrators should implement application whitelisting policies to prevent execution of untrusted binaries, while also monitoring for suspicious network activity related to the exploitation of this vulnerability. The vulnerability demonstrates the importance of proper input validation and bounds checking in software development, emphasizing the need for defensive programming practices such as stack canaries and address space layout randomization. Additionally, users should be educated about the risks of entering registration codes from untrusted sources, as this vulnerability could be exploited through social engineering attacks where malicious registration codes are distributed through phishing campaigns or compromised download sites. Organizations should consider implementing network-based intrusion detection systems to monitor for exploitation attempts targeting this specific vulnerability pattern.