Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DD23DE70A00820775577EAC5FD60BF4D7693F30BD60A84186EAE02A58FCBDB0B867D65 |
|
CONTENT
ssdeep
|
768:o9EsoRlMN7u6FXZEdZm+nAw/JR1o6TIpPi4NmQ58euKQh1Pwe/lCLuHD+8AfzT1B:oJoRlMN7u6FXZEdZm+nAw/JR1o6TIpPt |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
99997666266626d9 |
|
VISUAL
aHash
|
1818181818181800 |
|
VISUAL
dHash
|
b2b2b2b2b2b23030 |
|
VISUAL
wHash
|
3c3c3c383c3cbc3c |
|
VISUAL
colorHash
|
38000000c00 |
|
VISUAL
cropResistant
|
37c2462c5b54599a,8ace66676767c688,b2b2b2b2b2b23030 |
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 34 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.