Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D4B49EB1E52C15BF00574BCAD7617E4C232EE27BF69588906A6C45A01FE3CA4FD5F8A0 |
|
CONTENT
ssdeep
|
12288:ml/aQpQ90M37heoHrcwVOBhBxf1Whbv1ifUQjQDm:QQ1/HrtV8hBxN20UQjQDm |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
93832d2dac83a7b6 |
|
VISUAL
aHash
|
fb6e6e7c14400400 |
|
VISUAL
dHash
|
43dcccc8a4929c05 |
|
VISUAL
wHash
|
ff6e6e7c104a4800 |
|
VISUAL
colorHash
|
38001000080 |
|
VISUAL
cropResistant
|
43dcccc8a4929c05 |
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)