Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10911ED9D80240A6702529594B3D3A3097FC08946CB472F001BE8A69D2ADAF49C99A2C9 |
|
CONTENT
ssdeep
|
24:hR/CYHERDuVcUmTRk2NCA09bVE9i7Lyq5+:TlERDun2+b8IH+ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ac1ed3e12c3e92c3 |
|
VISUAL
aHash
|
ffff9f93f3f3f3ff |
|
VISUAL
dHash
|
2082393696060608 |
|
VISUAL
wHash
|
f0f09c9090f8f2f4 |
|
VISUAL
colorHash
|
07000001180 |
|
VISUAL
cropResistant
|
2082393696060608 |
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 4 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.