Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DCE239B4A230D335B1C24BE8DA642528765FE1DCD7C695B0F388AF51B0D6CE8D9260CB |
|
CONTENT
ssdeep
|
384:Y7fUWeguBTyoRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsaWRWEMd:Y7fUWegug2hhPhleMeDGCSPxeeWmHrW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3383f9e6eb108c9 |
|
VISUAL
aHash
|
00666060f0767660 |
|
VISUAL
dHash
|
5cdcdac3c3ccccc1 |
|
VISUAL
wHash
|
806660f0f0f6ff70 |
|
VISUAL
colorHash
|
30200e00000 |
|
VISUAL
cropResistant
|
81b0e170f4ecf0d8,1008323232080000,5cdcdac3c3ccccc1 |
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 68 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)