Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15CF23932F980E0662163AFD0B151BF3B6AD2EF37D1B9494415E801D78ECED7176A89E0 |
|
CONTENT
ssdeep
|
384:Z996+TRc2IM+hu30JJMLcj7TPe05ZVhXDpIdPYsJRzo:Z9Mv1QEb5dXDpI3i |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c355aebc30be4562 |
|
VISUAL
aHash
|
0000600000ffff00 |
|
VISUAL
dHash
|
16c9c8c8c0422b41 |
|
VISUAL
wHash
|
0270706c60ffff61 |
|
VISUAL
colorHash
|
301c0000000 |
|
VISUAL
cropResistant
|
024a5b2b2291c905,8611c8c8c8dcd822,8bc92501012581d4 |
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 24 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.