Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BC628470A050193F1AA74CE070A5B71BB597E30FC66F51C46BBC43D92FE3CA1AA57288 |
|
CONTENT
ssdeep
|
192:iBfW0BQ7Qi1wkREU+0gY23cxr7x/s3Q3Y+gVr435xMq85CNVrPad3X39UxMq8m9S:j7QDAWomQY+yr4rXrPaZHaPrVg6O |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a7d22dda25e207d8 |
|
VISUAL
aHash
|
ffffffffffffff00 |
|
VISUAL
dHash
|
4da8680c100a000a |
|
VISUAL
wHash
|
ff1c3c00f3f30200 |
|
VISUAL
colorHash
|
07001000180 |
|
VISUAL
cropResistant
|
4da8680810000000,04034aaabb1a0a01 |
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 1057 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.