Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11424D8743261663EC1A387F1F1B9673A61BA474DD917CC19F3AC92A717CAC84A833784 |
|
CONTENT
ssdeep
|
6144:JbWGgOuiRdNzdMiM0MwM9MMMgMNMfM/MFMNMSM3MYRWhSnZknjRcHgJB7Nr+ouGb:NWauiRdN5frBeR1aMiocJc9RWhSnZknj |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
936d3c31e496e139 |
|
VISUAL
aHash
|
02000c7c6c6e0e3d |
|
VISUAL
dHash
|
d638d8ccc8d8386d |
|
VISUAL
wHash
|
0e0c0c7e6e6e0e3f |
|
VISUAL
colorHash
|
30600018000 |
|
VISUAL
cropResistant
|
8000200c0c040000,d638d8ccc8d8386d |
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 28 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.