Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A0E229B49230D335B1C24BE8DA6425287A5FE1DCD7C695B4F388AF51B0D6CE8D9260CB |
|
CONTENT
ssdeep
|
384:Y7fUWeguCTIRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsUgRWmMd:Y7fUWeguPhhPhleMeDGCSPxeeWmH9W |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d1633ebc681f1c68 |
|
VISUAL
aHash
|
806660f0f8de9f90 |
|
VISUAL
dHash
|
5cdcdad391346c31 |
|
VISUAL
wHash
|
806626f0f8debf90 |
|
VISUAL
colorHash
|
38018000600 |
|
VISUAL
cropResistant
|
f8b2b4c192c6c5ce,00100c4c4c0c1008,5cdcdad391346c31 |
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)