Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17BC2D6ACF955A6B3612343CF73666B6871F0C347CF8A6581B7E8535C0BD2C25EC160AA |
|
CONTENT
ssdeep
|
384:n3jjMdT+T3Okpdk/7VTkEkPo6kX1kUk/FjjMdTR/xHk5:3jAdT+T4ZajAdTq |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ed6d92926d6d482c |
|
VISUAL
aHash
|
f9dbd1f393dfffff |
|
VISUAL
dHash
|
2332321636380323 |
|
VISUAL
wHash
|
998b91c1828ec3ff |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
2332321636380323,e4723d0e87c7c1d0,996c76160b0349c8 |
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 70 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.
| ID | Portugués | Inglés | Trigger |
|---|---|---|---|
Pages with identical visual appearance (based on perceptual hash)