Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15D6429457611712A41E720D6A43F060E723AEBA9A207850CF15AD6FC3E6CC8D92FFB75 |
|
CONTENT
ssdeep
|
6144:+xTPZmuCMEbopphce9u7Chn1S/Y7nHQJLs33oSNF92xoNq:uPZmuCMEEpIou7CXPnOLNSNFU |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
caa1963d536cd2ac |
|
VISUAL
aHash
|
fffff9001810103c |
|
VISUAL
dHash
|
83d8c13371f1b2e8 |
|
VISUAL
wHash
|
fffffd001810183c |
|
VISUAL
colorHash
|
02000000043 |
|
VISUAL
cropResistant
|
0000808000808000,0000d4d0d0c40001,56534d5d53512466,8aca0cd69218a6a3,ada562a9b164139b,8080825edec28090,606064646ce2c317,000010cbeb014000,81b3b371e1b2f1e8 |
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 57 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.