Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19562077231916B7E15AB87A8F2D4F32C6266A70DF9639851D3DB022B1FC2D97CC245C8 |
|
CONTENT
ssdeep
|
384:CGu8thE+T7cXbEP37DNmS7O8ynG0g7Fara+aVlIQ:CGu8thE+nR3PNmSq1c7I+9VKQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b6e3c91c2ce33338 |
|
VISUAL
aHash
|
ffffe7e38183ffff |
|
VISUAL
dHash
|
88000c0f3b2b00a0 |
|
VISUAL
wHash
|
4fcfc3818181cf4e |
|
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)