Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T167C253A04191E92302EB84E665768B6B31F5830DCD970205F6FD87F90BEEC9DEE17452 |
|
CONTENT
ssdeep
|
192:/FMQF+JJl0irDCZLcJBjRQQNfU7BRQzrSfHvGJ8O0XyoKxJlsSr0N+dg:/gAgJLFNfcByufPGJ8VXyoKxJlsVN+u |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b36666669923cccc |
|
VISUAL
aHash
|
e7e7e7e7efe7e7ff |
|
VISUAL
dHash
|
4d4d4d4d4c4d4d5a |
|
VISUAL
wHash
|
27030703e0e0c0ec |
|
VISUAL
colorHash
|
07006000000 |
|
VISUAL
cropResistant
|
4d4d4d4d4c4d4d5a,7d8e8b8f8acfbea2,80daa5a4a4a4a55d,c3e7fc5e73130101,d23133252d263635 |
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 4 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.