Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T182710DB0504C9C3E5382C3C48372277E339AC28BEA47171457E9DB9E9BD7E92DC240A5 |
|
CONTENT
ssdeep
|
48:TIRGxiUOW7L0dAk1PR0dck1MRGypf0d6eHd+MqpgVIHSlSFB8h9zOQ20wjHw2:TXojK0JBR05Xd66+4VaSlSFczmLr |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f9e5461aa0a15e5e |
|
VISUAL
aHash
|
10f0f0cfdc1c0c00 |
|
VISUAL
dHash
|
b1a2029a38383818 |
|
VISUAL
wHash
|
38faf8dfdc1c1c00 |
|
VISUAL
colorHash
|
38007008000 |
|
VISUAL
cropResistant
|
b1a2029a38383818 |
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 4 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)