Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12B52C5655E9868FA304BC6F5FEA55F8EA0C9508EDB326490F3FC021A93CAC76CD85581 |
|
CONTENT
ssdeep
|
192:lm7fmvpd+ljCs6Po+aoAcXpcxL8vzMYA+T:lmTmyVq7O5IwYAg |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e6629973c8cc6699 |
|
VISUAL
aHash
|
e3e7e7e7e7e7e7ff |
|
VISUAL
dHash
|
0d4c4d0d4c4d4c30 |
|
VISUAL
wHash
|
c1c3e7e7e7e30000 |
|
VISUAL
colorHash
|
07002440000 |
|
VISUAL
cropResistant
|
0d4c4d0d4c4d4c30 |
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 13600 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.