Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16A128430D0611D2FA22B95D1F4307B5930B7E70FCB595D68B2BD02EC5BE2DD4A82B1A6 |
|
CONTENT
ssdeep
|
96:P49oMtRwpD9XWkvtYxzCzlzdzhQ6UyQn58yYwWYdYsYNjZXu/4vUwCq7mVTeSF/:PW18pD9XWkvtEeZxC6bm/4vRuKw/ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b0347ed0bb0f454b |
|
VISUAL
aHash
|
86c700076f6e18a5 |
|
VISUAL
dHash
|
8c8c5eae9cdc734d |
|
VISUAL
wHash
|
04c700476f7ebda5 |
|
VISUAL
colorHash
|
38001000180 |
|
VISUAL
cropResistant
|
fcfcfcfce8f87030,f0f0f0e0e0f8e0ea,8c8c5eae9cdc734d |
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 12965 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)