Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C683F8B1B3C127329543D271ACCADEE4B279D508F3490096D39CC6A956A0C6CDBBBDD8 |
|
CONTENT
ssdeep
|
1536:jK44p23sEEOJm1uyctuhJnI0eF5HjiMewFQIHllpt1snFUg0XvHdE4vindghbIpl:rbZ3R/le |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a3831c3c6cc7c36d |
|
VISUAL
aHash
|
002f6f6321efed00 |
|
VISUAL
dHash
|
a6cbcbc363c9a923 |
|
VISUAL
wHash
|
002f6f63b1e7ed01 |
|
VISUAL
colorHash
|
08038000000 |
|
VISUAL
cropResistant
|
a4ad314d4d4d3149,a6cbcbc363c9a923 |
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 175 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)