Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FB83F8B1B3C127329543D271ACCADEE4B279D508F3490096D39CC6A956A0C6CDBBBDD8 |
|
CONTENT
ssdeep
|
1536:YK44p33PEXOJm1uyctuhJnI0eF5HjiMewFQIHllpt1snFUg0XvHdE4vIndgXbPpl:3wZ3R/le |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e303183c6cc7d36d |
|
VISUAL
aHash
|
002f6f63e1efedc0 |
|
VISUAL
dHash
|
b2dbcbc363892923 |
|
VISUAL
wHash
|
002f6f63e1e5edc0 |
|
VISUAL
colorHash
|
08038000000 |
|
VISUAL
cropResistant
|
a4ad314d4d4d3149,b2dbcbc363892923 |
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 150 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.