Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14782F96AB61423B44E4343EEFF1323EEE21341ADA69216CCE3B98119B1D58EDC575EC1 |
|
CONTENT
ssdeep
|
384:QeFou30UIXlEWPVyR1skdpssmMpBZ7eg/B:ToZEWPus6tm4/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f72a552a55a2dd0a |
|
VISUAL
aHash
|
00e3ffe7e7ffe7e6 |
|
VISUAL
dHash
|
454d0b4d2b0e4d0a |
|
VISUAL
wHash
|
00c381e3e7e7e7c2 |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
454d0b4d2b0e4d0a |
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 487 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.