Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10002B6115106506E81B767C8B9F25B08227EC39ED7130A5DB3ED2AB9A7CCC9D683389D |
|
CONTENT
ssdeep
|
192:vERzxaaC0l/lal4b1l1VONJ5+eOsMRiOd:vERzxXxNA4TPONSd |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
eb4e96d040f3c0f9 |
|
VISUAL
aHash
|
0000000000ffffff |
|
VISUAL
dHash
|
f4333353aa8c5516 |
|
VISUAL
wHash
|
3c11810000ffffff |
|
VISUAL
colorHash
|
13002000041 |
|
VISUAL
cropResistant
|
800080c0c0c28080,6c4dc567a53434d2,0000000008000000,aaa4555557962955,d4333333131345aa,88696928baaa3a3a |
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 46 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.