Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BE5396B06E580D7E968347D7DBD23F9572A994D7E20246E4F3E44A4C0FC2D6CC9CA2A1 |
|
CONTENT
ssdeep
|
768:Vyi+raFRXjip8pSkbkY3qAtYdhYvk1r4s9cU:VtHahYvkyvU |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bb193dc1c1e5c4ca |
|
VISUAL
aHash
|
af8d9dc1cde78187 |
|
VISUAL
dHash
|
5b39290b190c2b2b |
|
VISUAL
wHash
|
bb8d8f81c5878387 |
|
VISUAL
colorHash
|
07e00008008 |
|
VISUAL
cropResistant
|
5b39290b190c2b2b |
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 159 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)