Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T157A364726025ECB711A3A5D1B5B4630F32AAC71BDE034787B7F49BAC5AC6E94ED23410 |
|
CONTENT
ssdeep
|
768:W8GM2w4ll3QfkKQ8E3LDrE9UxqEZxQ6PMLfW+3LyO0rBJ2d46xey:Apll3Q9E3PbQpLe+7y9/JAT |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
922f7cd247382717 |
|
VISUAL
aHash
|
00ff00047e7edefe |
|
VISUAL
dHash
|
d45e1fddd0fcbcbc |
|
VISUAL
wHash
|
00ff00043c7edefe |
|
VISUAL
colorHash
|
03000000c00 |
|
VISUAL
cropResistant
|
800036170e62001f,6c7eeeda9a9a9a9a,8e96f4dddcf0ca8c,5d1fdcd0dcb4bcbc |
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 98 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)