Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13A326838B284283E725787AAF674773C51BAC38BD207876CF77981E16382D59DD23290 |
|
CONTENT
ssdeep
|
192:8pF4CMk9qYZCsjIZ2ZoMZj2ZHnZM2ZS8Z82ZcZAkN:8pF4CMk9pCum2R2ta2s2jkN |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ee6a93924e669139 |
|
VISUAL
aHash
|
ffc18191f1ffffff |
|
VISUAL
dHash
|
492b032323080f32 |
|
VISUAL
wHash
|
a1818181b1ffe7b3 |
|
VISUAL
colorHash
|
07400000180 |
|
VISUAL
cropResistant
|
492b032323080f32,e0e4ccd4d4cce0f0 |
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 12 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)