Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11561C91040480F3FA28387B8F7A27675A19FD389CB575584E2F5423913C2C51CD636B1 |
|
CONTENT
ssdeep
|
48:Ty5upBkIjHcdw24ajPakwxR1TBugwm2r1TH7InS+t8t18T/QgI18yeequbQ:T+ufRIakwxRB0gw5BHyS+yO/DI/eeJQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc3333cc66339966 |
|
VISUAL
aHash
|
0000181818180000 |
|
VISUAL
dHash
|
0000103030300010 |
|
VISUAL
wHash
|
000018181c1c0000 |
|
VISUAL
colorHash
|
380000001c0 |
|
VISUAL
cropResistant
|
0000103030300010 |
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 30 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)