Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T197442BE27285723A41432C6C5CBBDE98B7798A40C14A1064D1A9C1E1FEF8CB6CE7DDD9 |
|
CONTENT
ssdeep
|
6144:2krckXLPL/h0c28fpG4Xar/gK1egT9pJRmxPnThQ/HW9kILgb1:9ckXLPDh0c28fpG4Xar/gK1Okjb1 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8956a7702799d28f |
|
VISUAL
aHash
|
00003c1800d8db83 |
|
VISUAL
dHash
|
9468693073b0b303 |
|
VISUAL
wHash
|
4e3c3c3c18d8dbc3 |
|
VISUAL
colorHash
|
38000007000 |
|
VISUAL
cropResistant
|
c685392bab23a685,a280908c8d8ca0a2,803b7736606c6c60,9468693073b0b303 |
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 665 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)