Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11A421BB5B72412E0DA0387DBFF2222FAA103817ED9525ADCD3648718B2E9DFD8954DC1 |
|
CONTENT
ssdeep
|
192:QoQHoB6CJ54t9IRzLmx2xPewKdC8ku9cuGRmKbMpBXp7sfgg8gk:QnoCULmx2xWwKdSsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bf8ad52ad56ad084 |
|
VISUAL
aHash
|
8181bf81818181ff |
|
VISUAL
dHash
|
173f793373333316 |
|
VISUAL
wHash
|
818fbf99818181ff |
|
VISUAL
colorHash
|
07006000000 |
|
VISUAL
cropResistant
|
173f793373333316,1e3aedcace6c44c8,b2fdf869f1f860f3 |
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 490 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.
Pages with identical visual appearance (based on perceptual hash)