Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T163138374231C3E3D690787E4F365BB69526CA290EA2AD16CD2BD267213C7CC4F8279D4 |
|
CONTENT
ssdeep
|
768:om1O2LDsAYYYYlYYYYzYYYYdYYYY0wZRi38T2rP0OUWq:N1O2JYYYYlYYYYzYYYYdYYYYisR |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a2630808f7663fdd |
|
VISUAL
aHash
|
00ffffe7ff0000ff |
|
VISUAL
dHash
|
d080080c08b1b580 |
|
VISUAL
wHash
|
007fe7e7ff08004e |
|
VISUAL
colorHash
|
07000010180 |
|
VISUAL
cropResistant
|
0c3232324c483232,408080d0d0e080c0,90880c0c00b5b188,80408080d080c000,4501854185850585,240b2b2b2b2b0b24 |
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 230 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.