Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1605242305218383F93339BCCBBAD73B9219B7142C54E1568F6BC04B99381E89ED3759A |
|
CONTENT
ssdeep
|
192:3Gu6AsAZvIanXbD0c0i0PZ4zX1VauUWqW64I:3GwtZvfrD0c0i0mX1VauUWqWPI |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
94b594b594b594b5 |
|
VISUAL
aHash
|
fe0000000000003c |
|
VISUAL
dHash
|
a641000010000069 |
|
VISUAL
wHash
|
ff8f0f0f3030003c |
|
VISUAL
colorHash
|
380000001c0 |
|
VISUAL
cropResistant
|
a641000010000069 |
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 32 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)