Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17661403515280E3B01C3D6E9BBA4AB0776C3C34AC793260923F893985FC7C96CE9A161 |
|
CONTENT
ssdeep
|
96:Tkp7DGeHgxU5M/OynmN0UGhGCkgD10uhkp:Qp7DLHgINM7k26p |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3338b891933b399 |
|
VISUAL
aHash
|
ffffff0000ffffff |
|
VISUAL
dHash
|
0c28080c30000000 |
|
VISUAL
wHash
|
e4e4e70000ff0000 |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
0c0c0c0c08004d0c,0000000000000000,1008323210080000 |
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 48 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.