Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15ED2A6347284492EB54BC6E5F6B1372858BFC307C25F906CF9A442B6138BD99DC376A8 |
|
CONTENT
ssdeep
|
384:3KmHpF25fqras3z9/eJqtN9K4zsuzFSTqjmWk:3nL25irau9/eJqtNxz8Yk |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bc4643bcbc83c33c |
|
VISUAL
aHash
|
000000cfc7ffffff |
|
VISUAL
dHash
|
22c4c03e3f3c1c34 |
|
VISUAL
wHash
|
000000c783ffffff |
|
VISUAL
colorHash
|
07000000007 |
|
VISUAL
cropResistant
|
0020202323240020,3c3e3f3fe83c3438,10c0e4e4e4c4c410,fba9b9ae76f8fdfd |
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 4 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.