Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BCA15431640965270123A9CDE0713E29D9A3F71FC336F96161E6032A9ECBE52EE4F478 |
|
CONTENT
ssdeep
|
96:JT+SgVysqa040ju0SK0uUPpg/Sd+Lyu0u6bc+S4+1J:USgVysozjp4pPpP+2jU1J |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e5659999ce656898 |
|
VISUAL
aHash
|
fbc3c3c3f7ffffff |
|
VISUAL
dHash
|
038e8e8646162228 |
|
VISUAL
wHash
|
f1c3c0c0c3c3cbcf |
|
VISUAL
colorHash
|
07e00000000 |
|
VISUAL
cropResistant
|
038e8e8646162228,73632d7b68747667 |
Victim enters username and password into fake login form. Credentials are captured via JavaScript and exfiltrated to attacker's server in real-time.
Malicious code is obfuscated using 5 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer supports multiple blockchain networks and checks for high-value tokens on each chain before executing drain operations.
Pages with identical visual appearance (based on perceptual hash)