Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13AF2FF21A86E643F0173B6C0E8E79F5168E2520FC6524664D3FF925D1BDDEB4F823922 |
|
CONTENT
ssdeep
|
384:6Q1HcOOjcK8235HUZKSkQvTwOQNumGn+RB3ty3zekzeAze9zeTzeibzeATzeAqzW:xHVOjcKF35aJkQvTwOkut+dYvj |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8630f3c4ec3b132f |
|
VISUAL
aHash
|
ffff01010304ffff |
|
VISUAL
dHash
|
00fcffbfe7e8694d |
|
VISUAL
wHash
|
ffff00000000ffff |
|
VISUAL
colorHash
|
070030000c0 |
|
VISUAL
cropResistant
|
00fcffbfe7e8694d,2d29e12d5b36f7d9,ffffbfaedcbcf93d |
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 1300 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.