Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T171B209E5A720853C41575BAEF9333A38A25BE09EF5161940C67CCBE68BD7EE0E407235 |
|
CONTENT
ssdeep
|
384:Z4gPg6kbnMF8hKQ0XoyI3axsSXEw8GFjCXwU4lrkYkhKQ0kVFRziYhFMooi6S2nV:2cUQF6KQ8o1tC8KQH9imoi6Ssuu31P6O |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9ae364acb1d3c62c |
|
VISUAL
aHash
|
ff003c3c3c3c0000 |
|
VISUAL
dHash
|
0e71615975617996 |
|
VISUAL
wHash
|
ff003c3c3c3c08bf |
|
VISUAL
colorHash
|
02000e00000 |
|
VISUAL
cropResistant
|
2e31617979656951,c0e43a183af48001,0000000000000000,a761615975617996 |
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 223 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.