Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F283541CE755217EB02383C8D7F33A32334BA28F8701C110DB6655B26AA68EDAD675F5 |
|
CONTENT
ssdeep
|
1536:F6Mo7Q5SQxbeudAd6QloXaQCcE4QnCnmCWV+Qxk2kMkgk1BAoQ9tE+Q8PTECVEzR:FvF |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3333331cccccccc |
|
VISUAL
aHash
|
c3c3ffe7e7ffffff |
|
VISUAL
dHash
|
4d4d080c0c1c1c0c |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07000030000 |
|
VISUAL
cropResistant
|
4d4d080c0c1c1c0c,4c7c70727270387c |
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 23 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.
Pages with identical visual appearance (based on perceptual hash)