Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D4E222B0D1548D7B00EBE1C6D730BB4B72E2929ADA67470207F89B695FDBC90EC13499 |
|
CONTENT
ssdeep
|
768:HJFx856VMWAzhZzsJNJzo1zz8vzqCzui72zCW3zCPwbcbglTaHSQ6wFUPL4cudmR:LxUZFI/GbOx4eg+1p/1ALlHBBorQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e94d621646736d4d |
|
VISUAL
aHash
|
00fbfbefff83cbff |
|
VISUAL
dHash
|
4d121212203f1b23 |
|
VISUAL
wHash
|
008bdbebbf8181f1 |
|
VISUAL
colorHash
|
07000000640 |
|
VISUAL
cropResistant
|
4512121a203f1b23,0003036323034300 |
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 12 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)