Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E8242A693641BA2317EA82DB506B8043F3395559280E093CB66CDCDA757898A71FFFF0 |
|
CONTENT
ssdeep
|
6144:nZr+ouGORhg+rxwRkADhoz/dasuPyHDymwJJd3+GRhLfcKQCdgdonTeET29MjRnZ:lBJ+rmRnyHDymwJJd3+GRhLfcKQCdgdq |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3337e4c4c6c3233 |
|
VISUAL
aHash
|
000f07ffffffffff |
|
VISUAL
dHash
|
05d838c2c2c80400 |
|
VISUAL
wHash
|
0007043b3b7bf0f0 |
|
VISUAL
colorHash
|
06000000388 |
|
VISUAL
cropResistant
|
cc3a3a82d2ca0800,c0202021212120c0,0303aa8a898c8c8c,0686a98372888890,00a69088a8808800 |
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 28 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.