Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CFC295243540367F1D7B8AB8B7C4F20B664ED21CD577A1BAA6DD107A33DBD90CA139A0 |
|
CONTENT
ssdeep
|
768:yYkYIYKYm9dKY7eHYLYIkdKY7LXGXCXhX2XOXAXcXqX4XFXpX4XJXXfwO0RXxY/x:2NeWkNCUIx |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9313ececec698998 |
|
VISUAL
aHash
|
000c0c00ffffffff |
|
VISUAL
dHash
|
39dcd8d8260a4c10 |
|
VISUAL
wHash
|
00040000fffff7ff |
|
VISUAL
colorHash
|
17001000046 |
|
VISUAL
cropResistant
|
002b2b2b2b2b0204,e070668151c425a5,00262e324d4c9012,23d8d8d85cd8d827 |
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 22 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.