Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CB5387709146627322AB49D3F0B7630FB1E7E74ACE97964927FDA3E44BC6C99BC09041 |
|
CONTENT
ssdeep
|
1536:2C9CyP3y0QaXo3q6LIEbFP/f0QaXo3q6LIEbFP/WvnHlrgvUx6q4:fC |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e6cc6626cccc3366 |
|
VISUAL
aHash
|
e7e7e7e7e7e7e7e7 |
|
VISUAL
dHash
|
4d4d4d544d4d4d4d |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07400210000 |
|
VISUAL
cropResistant
|
0202020202020202,a0a0a0a0a0a0a0a0,c69eaaaaa2a833b2,848a60ccd4606060 |
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 1365 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.