Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1AED55CD2B243B8214B9B91F5C8BF642EE337140D8945C081F6D5C95E3B6EE8511E2BBE |
|
CONTENT
ssdeep
|
24576:9X3eUddSeKSU4tClOUewCol7M7qR8bM7kR8bM7xLkdSOhGXsytINL8G2S:9XDdSeKSU4tClOUewColILkcOMXsYI5Z |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cd9e3232260ccd77 |
|
VISUAL
aHash
|
263c38183c181800 |
|
VISUAL
dHash
|
cc707071f0707004 |
|
VISUAL
wHash
|
7ffc3c3c7c3c1800 |
|
VISUAL
colorHash
|
31400018040 |
|
VISUAL
cropResistant
|
9c0ece899ece8e96,9280968696a280b2,cc707071f0707004 |
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 1184 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.