Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DCE322E9DC0B29BE404BE6F8D52252157ED6EE458F52EA2A83F387254B36D0CDDD3018 |
|
CONTENT
ssdeep
|
1536:AIjKBbnPi1BpDxUNhU0o5YHsCmqwOJ51IjBYTqJ9TULCClKClUCluQRuLDm3X/bQ:zClKClUCl7ul |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
92136c6dfc056d96 |
|
VISUAL
aHash
|
000c2c2c0c003cfc |
|
VISUAL
dHash
|
dc69c9c9c9c2d829 |
|
VISUAL
wHash
|
060c7e6e0e007eff |
|
VISUAL
colorHash
|
3920a010000 |
|
VISUAL
cropResistant
|
ccd4d8d0b2baaeb2,a001494931390990,dc69c9c9c9c2d829 |
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 8 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)