Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E103817923482E7D65178BE8FBA4B769126DC294FA6B9568F3BC017123C7C45E8332D0 |
|
CONTENT
ssdeep
|
768:2zwsDYmj+S7IV2+ls0kkkklkkkkekkkk5gc3:Zkkkklkkkkekkkk5gy |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ad46323dc1fb92c1 |
|
VISUAL
aHash
|
000000ffff8b81ff |
|
VISUAL
dHash
|
35c46822962b2b10 |
|
VISUAL
wHash
|
000000ffffcf81ff |
|
VISUAL
colorHash
|
07000000030 |
|
VISUAL
cropResistant
|
0001436363000001,c4cc7112182b2b00,34ccc8c8d396d2da,9125d4c4ccc44469,ccac273836390c12,ecac273836390c12,1d4c46b1c9d5d6b2 |
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 71 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.