Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EBA25E22A80112BB0867D4C89663BF6B39DAF31AC28B550026FD01568FD7F727D6E671 |
|
CONTENT
ssdeep
|
384:lnsBT9IwDiDm+FHq882X82Y82alPWBUdF:qBT9IwIm+rlPWBUdF |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a62434343ed2dadb |
|
VISUAL
aHash
|
0000ffffffffffff |
|
VISUAL
dHash
|
a6d60169494980a2 |
|
VISUAL
wHash
|
0000a5a5bdbd7e7e |
|
VISUAL
colorHash
|
07008000e00 |
|
VISUAL
cropResistant
|
a6d60169494980a2,b1a999c9d52dd4e4 |
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 20 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.