Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BCE22EB1A504253B522749E174B1AF9FB5D3930ECB670800A7FC83D96FCEDA4CC692A5 |
|
CONTENT
ssdeep
|
384:leHjfhQe4goTX+XPfXUkX2IXKAXBkXfJOxorRqt36qkEJ9ZMhB:iOjOxoVqQqr+ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ded0f4c632d27132 |
|
VISUAL
aHash
|
7c3c181c043c3c00 |
|
VISUAL
dHash
|
d470d0714961611e |
|
VISUAL
wHash
|
7e3c3c3c343c3cc8 |
|
VISUAL
colorHash
|
38000006600 |
|
VISUAL
cropResistant
|
d470d0714961611e |
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 95 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.