Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12463A56422083E3E652386E5F3E4FB6452ADA295E757855CF2FD113127C6CC4F827B84 |
|
CONTENT
ssdeep
|
1536:bvPZlemRgbawtOFgla9m9v9N9MF5gla9m9v9N9Mpgla9m9v9N9Mkgla9m9v9N9M6:b5Lf |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a67699d926cc8999 |
|
VISUAL
aHash
|
ffe7e7e7e7e7e7e7 |
|
VISUAL
dHash
|
0c4d4d4d4d4d0ccd |
|
VISUAL
wHash
|
0003000000008404 |
|
VISUAL
colorHash
|
072010080c0 |
|
VISUAL
cropResistant
|
0c4d4d4d4d4d0ccd,b4b6f2680483d4c4 |
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 63 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.