Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C59140343269B437037B79DA75A2A73AF4EB6179D7592C20E6EC47CD83C9C61A805123 |
|
CONTENT
ssdeep
|
96:g11nd/7dSW3LSZSZSTdAGalAyz0+ka1ZDJJJS4AG1rd30ItkebCe:id/7MXIIZHGX0+L39bNv1/vbCe |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9313ecec65e1e42c |
|
VISUAL
aHash
|
000c0c0c00ffffff |
|
VISUAL
dHash
|
d8d9d9d9d9261800 |
|
VISUAL
wHash
|
000c0c0c0cffffff |
|
VISUAL
colorHash
|
06001c00000 |
|
VISUAL
cropResistant
|
a3b35adaf0c03333,0824246969488800,8020000000000000,d6d9d9d9d9d9d999 |
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 14 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.