Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CB04A8B7E204516D43A3D3DC97B13439E25355ADEFC6054AE2948AE770C1CF8C8AE8A7 |
|
CONTENT
ssdeep
|
1536:WgedrGF/UEMGucIXbppDlOfMqYyZvS+ZTMb0b8vOunJIiQrnr1UAMG4Sz8g7f1mY:gduzI+gOunJhPOOunJhPn |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8fa5f0875bf0055a |
|
VISUAL
aHash
|
7fff1f1d3d3ffcf8 |
|
VISUAL
dHash
|
5169756969606969 |
|
VISUAL
wHash
|
3f3f0c1c1c3ffc00 |
|
VISUAL
colorHash
|
07000008441 |
|
VISUAL
cropResistant
|
5169756969606969,f6f2b61131aaaaf2,e648e8c88ae6e6f1 |
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 2218 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)