Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1643285762188113E423B07AD3C306B6C727BC1AEC76B6D0075AC8E9DEEC59469E059C7 |
|
CONTENT
ssdeep
|
192:ZERzxPb+DiS5NuEwHPn6soSU1kkA7JJVD7vBW41K8:ZERzxPb+Di+EEw/6XSU17A7zVD7vBWy7 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ce4c15574b1b935a |
|
VISUAL
aHash
|
00d0f0f0f0ffffff |
|
VISUAL
dHash
|
c416956525aaa003 |
|
VISUAL
wHash
|
00400080f0feffff |
|
VISUAL
colorHash
|
062010c0000 |
|
VISUAL
cropResistant
|
800080c0d0c08080,96955525a8ba2803,d0c816f683979545,67eedb634987e763,8c66d39884e5cd4a,b39213316771b1b6 |
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 46 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.