Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16143F371720536BB056BB5C06C21AF89A0C6D7A6C113C18596FDA1220FC7FF2EF4A5B9 |
|
CONTENT
ssdeep
|
192:dR72G2IX1KrQ0T2Bq6AYcoZJjKRmUZ9jnP2Zu5tWvluhGmMRb09Fndxoj9QszFbl:LqwKzmus4clFb6wBOhY/zOXEHHAVu |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
96942ccd6873da9c |
|
VISUAL
aHash
|
1f3f3e7e7c380000 |
|
VISUAL
dHash
|
fefefcc8f0e0c135 |
|
VISUAL
wHash
|
1f3f3f7e7e380000 |
|
VISUAL
colorHash
|
080020001c0 |
|
VISUAL
cropResistant
|
fdfcfcf898e4c0d0,fefefcc8f0e0c135 |
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 56 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)