Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12313EC30F886A9334183D1D5AF76471B76E0B30AD743470597F8C3AC6BDAD9AED06648 |
|
CONTENT
ssdeep
|
768:cUGvWV6B7ruLm/tDuPU2aCFP+Esc+Uw8bLH:cLvWV6BruLm/tDuPU2aCgEsc+t8bLH |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b333999999346666 |
|
VISUAL
aHash
|
cfe7c3c3ffffefe7 |
|
VISUAL
dHash
|
180d4d0c100c0c0c |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07000208080 |
|
VISUAL
cropResistant
|
180d4d0c100c0c0c,b3a398988ce6d491 |
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 15108 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.