Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12C2321319440D92B02EB9BC8A636533A22E68349C6130698FBF9C3F95BDFD6DD937444 |
|
CONTENT
ssdeep
|
768:hA/sIx/j2D2alAtdDXzSIm8l5SX/Py/2oJU5kkLUf7QGjH+K0Pa:hA/sIxqD29DXzS+PSX/Py/2GU5lE7QBa |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8af5d26a3b251956 |
|
VISUAL
aHash
|
ffff7f0301011000 |
|
VISUAL
dHash
|
1b03f7f7e3e7e5f1 |
|
VISUAL
wHash
|
ffffff0b01113000 |
|
VISUAL
colorHash
|
17400018000 |
|
VISUAL
cropResistant
|
3b03f7f7e3e7e5f1,9716e869a9746f7f,fc80c026b68080fc,18443adada5a5858,fff3ebe1f3e6f471 |
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 50 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.