Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17BE229B4A230A335B1C247E8DA6425687A5FE1DCD7C695B4F388AF11B0D6CE8D8160CF |
|
CONTENT
ssdeep
|
384:Y7/t2ukTyRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3As6uRWrsMd:Y7/t2uHhhPhleMeDGCSPxeeWmHCsW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c31e3cb163f34b48 |
|
VISUAL
aHash
|
801670e060766e00 |
|
VISUAL
dHash
|
4c34e6cbc3ccccc1 |
|
VISUAL
wHash
|
8016f2e070feff60 |
|
VISUAL
colorHash
|
38200448000 |
|
VISUAL
cropResistant
|
305092bea6e24a4a,8e9ab365666a4c74,2d1cdcc7e3f8fdf9,80100c4c4c081000,4c34e6cbc3ccccc1 |
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 70 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)