Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E293873426482B3E582BCBE8F7A4B326235DC355E52B916DE6AD127127C7C80ED339D4 |
|
CONTENT
ssdeep
|
1536:kaqDbeOVeLDmfgC33ccccKjcccc+wccccdQ3f7sOkgc0:EZgP6lT/ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a323dcb855cadc2a |
|
VISUAL
aHash
|
1f00000000ffffff |
|
VISUAL
dHash
|
7bcfcdcfce2e3230 |
|
VISUAL
wHash
|
ff00000000ffffff |
|
VISUAL
colorHash
|
03000038000 |
|
VISUAL
cropResistant
|
846b2b2b2b62d7ff,8d0d3333654ddce6,af002e623030c446,ffcfcfdde5cfcefe |
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 12 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.