Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CA921A36731022795E8783D8F67073DFA3038269D82796D9E3DA031936DAEEAC910DC5 |
|
CONTENT
ssdeep
|
384:QfoCdAY2WAYnAYqxaC5KfRI+26AE2M2smMpBZ7eg/B:IoMAY2WAYnAYq8YKfRI+1AHam4/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f72a552a5f2a5582 |
|
VISUAL
aHash
|
00ffff81fffffffe |
|
VISUAL
dHash
|
712409030d4d0d0e |
|
VISUAL
wHash
|
00dfff0081a1e7ee |
|
VISUAL
colorHash
|
07001000180 |
|
VISUAL
cropResistant
|
712409030d4d0d0e,0000083030100800 |
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.