Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T196D34325C6E41333D205078AD3DB7756269BC1C7CCA2B8F8A1708179DBBAD891C77DA2 |
|
CONTENT
ssdeep
|
3072:gsKhrjylK2E6IOZuagKI3ImJS2QgIYLQICeIkPksuGIyIhuBn1Ymy9:vKFQ5Idf3N+mE |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a512cdb226edce23 |
|
VISUAL
aHash
|
ff0f0b070707fbf3 |
|
VISUAL
dHash
|
3c98d6dccc8f13b3 |
|
VISUAL
wHash
|
ff0e0b030607f3f1 |
|
VISUAL
colorHash
|
07002000180 |
|
VISUAL
cropResistant
|
3c98d6dccc8f13b3,333733438626d656,cd8eacf5f56763c3,8696c4ec8c292c6c |
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 30 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.