Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17D33CC30B88699334193D1D5AF7A871B76E0F349C64347059BF8C3E82FDAD9AED06648 |
|
CONTENT
ssdeep
|
1536:GUB6j3GklF/1BKlM3xv89tVrHHpSK5jUi6euMwC8bLH:HolFa/C |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b332999999756466 |
|
VISUAL
aHash
|
cfe7c3c3ffefe7e7 |
|
VISUAL
dHash
|
104d0e0c101c0c0c |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07200208200 |
|
VISUAL
cropResistant
|
104d0e0c101c0c0c |
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 14777 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.