CVE Tools
Home/Vulnerability/CVE-2019-25701

CVE-2019-25701

Easy Video to iPod Converter 1.6.20 Local Buffer Overflow SEH

Published: Apr 12, 2026Updated: Apr 12, 2026 Sources: CVE List NVD
8.4CVSS
HIGH

Easy Video to iPod Converter 1.6.20 contains a local buffer overflow vulnerability in the user registration field that allows local attackers to overwrite the structured exception handler. Attackers can input a crafted payload exceeding 996 bytes in the username field to trigger SEH overwrite and execute arbitrary code with user privileges.

EPSS Score
N/A
CISA KEV
Not in KEV
Exploits
No Known Exploits
Remediation
No Fix Available

CVSS Vector Breakdown

AV:LAC:LPR:NUI:NS:UC:HI:HA:H
Exploitability
AV:LAttack Vector
Local
AC:LAttack Complexity
Low
PR:NPrivileges Required
None
UI:NUser Interaction
None
Scope
S:UScope
Unchanged
Impact
C:HConfidentiality
High
I:HIntegrity
High
A:HAvailability
High

Weaknesses

Affected Products

Easy Video to iPod Converter
Divxtodvd

Attack Graph

Products CVE Techniques Tactics

Click technique nodes to view MITRE ATT&CK details. Scroll to zoom, drag to pan.

Exploitability

No known exploits, KEV entries, or remediation guidance available for this vulnerability yet.

MITRE ATT&CK

2 techniques
Initial Access
Privilege Escalation
View detailed technique mapping

References

and 1 more references View all →

Timeline

Published
Apr 12, 2026
Last Updated
Apr 12, 2026

Unlock Complete Vulnerability Intelligence

Get the full picture for CVE-2019-25701 and every CVE in our database. Create a free account — no credit card required.

Create Free Account
AI-powered analysis
Plain-language impact assessment and exploitation scenario
Attack graph visualization
Interactive attack path and kill chain mapping
Exploit details & PoC links
ExploitDB, Metasploit, GitHub PoCs with direct links
Nuclei scanner templates
Ready-to-use vulnerability scanner templates
Full remediation guide
Patch instructions, workarounds, and compliance impact
Interactive AI chat
Ask questions about this vulnerability in natural language
Related vulnerabilities
Semantically similar CVEs and attack patterns
REST API & MCP access
Integrate vulnerability data into your workflows