Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T138520A712151277E116B8BECB1D8F32D636AA709F9639815E3DF022A1FC2C97CD245C8 |
|
CONTENT
ssdeep
|
384:Cn6uW6tH0I0i08O7cXbEP3NDNmS7O8ynG0g7Fara+aVlIwP:Cn6uW6tH0I0i082R35NmSq1c7I+9VKwP |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b6e3c91c2ce33338 |
|
VISUAL
aHash
|
ffffe7e38183ffff |
|
VISUAL
dHash
|
88000c0f3b2b00a0 |
|
VISUAL
wHash
|
43c3c3818181ff7c |
|
VISUAL
colorHash
|
0700a0000c0 |
|
VISUAL
cropResistant
|
88000c0f3b2b00a0 |
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 222 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)