Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T161E239B49230D335B1C24BE8DA6425287A5FE1DCD7C695B4E388AF51B0D6CECD9260CB |
|
CONTENT
ssdeep
|
384:Y7fUteguZTsRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsoYRWIMd:Y7fUtegukhhPhleMeDGCSPxeeWmHDW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3e13e9e783849e8 |
|
VISUAL
aHash
|
00666060f0262600 |
|
VISUAL
dHash
|
7cccdac3c1484c49 |
|
VISUAL
wHash
|
80666ef8f87e2f20 |
|
VISUAL
colorHash
|
30201000051 |
|
VISUAL
cropResistant
|
f683e18889b1b9dc,9d83d0e064b4b8d9,c1e4f6f2786c7637,7cccdac3c1484c49 |
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 72 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)