Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C6822D65B22421E44E4243D66D2123AFA11750BD7B5247DCB7A9C23CF6DA8FDC830DC6 |
|
CONTENT
ssdeep
|
384:QCoCTRba0ftLNQQFqJs98GmMsmMpBZ7eg/B:LoAV4s98Xm4/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c6db1919642d3b36 |
|
VISUAL
aHash
|
78fcf4f4f4fc0000 |
|
VISUAL
dHash
|
d1e9696d8de974c0 |
|
VISUAL
wHash
|
f8fcf4f4f4fc0000 |
|
VISUAL
colorHash
|
030000001c0 |
|
VISUAL
cropResistant
|
4c923333637193c3,d1e9696d8de974c0,7a5d5c6f66636d0c |
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 490 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.