Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A3A1C83211454C3B9613C2F6A8E1F38640E6C62DC15B9A45F3DD01BA2BDEEC1C9776B8 |
|
CONTENT
ssdeep
|
96:T4DnY8t46Yb4tSBkmBfY6HIh9cIK5k1Wjm7/GBz17:vXY4D7 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f8b00f0fec2d4d4c |
|
VISUAL
aHash
|
01cdc0c3f8f81010 |
|
VISUAL
dHash
|
1999969680a16263 |
|
VISUAL
wHash
|
01cfc6dbf8fc1818 |
|
VISUAL
colorHash
|
07001007000 |
|
VISUAL
cropResistant
|
1a12722e31304e4e,1999969680a16263 |
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 32 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.