Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13E33BC20622456B340B3D3D598653F2E3297F30EE50A9ED06FB4C2E92FC7CA1BD159A5 |
|
CONTENT
ssdeep
|
1536:uRywRyO9SXL9SXe9SXB9SXrfL1KoSc+J67FOr7DUHAN:U9SXL9SXe9SXB9SX1C7DUHk |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c94bb6b4e548c2ba |
|
VISUAL
aHash
|
ff8998f0fbffffff |
|
VISUAL
dHash
|
5979312373383301 |
|
VISUAL
wHash
|
bd08189089ff81ff |
|
VISUAL
colorHash
|
07007008000 |
|
VISUAL
cropResistant
|
5979312373383301,2756182d934e3918 |
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 35 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)