Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15653E0625526D83700E7A2D7A2B72B27A2F44388C5820146F6FCC3B917FEE59FA33415 |
|
CONTENT
ssdeep
|
1536:UsIxEUjTAy58PcYJa+Hkrp6W44Pj/s44PgXs44E7/s44EeGt44iMic44qAjc44nn:UGMbh7k |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c6136cb9e613ec83 |
|
VISUAL
aHash
|
a01e2604ffff00f0 |
|
VISUAL
dHash
|
487c4c4c4c324027 |
|
VISUAL
wHash
|
e01e2624ffff00f0 |
|
VISUAL
colorHash
|
110020001c0 |
|
VISUAL
cropResistant
|
a280d286869280a2,0c00443030000000,02004a030b0b0b0b,4c1838c44c2c4c4c,4020d0c814242527 |
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 40 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.