Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BB82F131E182A5373B1F89E5B53E5B49E6AAC708CA030E6923BD73F417D6E82DD27150 |
|
CONTENT
ssdeep
|
384:AKCbrDi//TC/zSx68sphS0EGcUDUtmWfxq9rg1Ys9Xi:AbrDiW/2x68sXjDcUHCxq9mYsk |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
87f41d9c9c166077 |
|
VISUAL
aHash
|
3eefe7ffff600000 |
|
VISUAL
dHash
|
70cccccccccd4d61 |
|
VISUAL
wHash
|
1eefe7efe7240000 |
|
VISUAL
colorHash
|
02007000040 |
|
VISUAL
cropResistant
|
70cccccccccd4d61,a3a6565292929666,4b2d1d1d1d1d4933,334ddc3394cc4d17,333b5e4c2e3b2337,dcdcd4d42369070f,e7f98e27a1c9c79e,0d6169696961170f |
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 95 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.