Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F1E273B1C68420EF2113CF95E8656B6B32CB916DDA33CD2047BC4F9DE7DADC08659886 |
|
CONTENT
ssdeep
|
384:gXM+dNzUFlcB7lGtim1pk7r2PPaL6/I8oJRHyRbATRTee7wycRT:20U7lAiX7U3/3RbATRbMt |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ec966c6c966c9625 |
|
VISUAL
aHash
|
f7ffffffffc1c1c1 |
|
VISUAL
dHash
|
2f02122023131737 |
|
VISUAL
wHash
|
81dfdb9dbd818181 |
|
VISUAL
colorHash
|
07e00000000 |
|
VISUAL
cropResistant
|
2f02122023131737 |
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 37 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)