Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BD33633060675537035BA1C2A2311B0EB3D6C385DA9317AA9BF987ADEFCBC94CC17661 |
|
CONTENT
ssdeep
|
384:Y+QrN+ppkwx/rNYZDmpIRNa9GI7lTHASTHzNk9Gs90s90l2Na9GlSDd4w6mUIN:8rgppljjAYlTASTGAs6s6hAlSDd4w6mD |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
93556d9b44a6d0e6 |
|
VISUAL
aHash
|
08085c7e7e0c0d01 |
|
VISUAL
dHash
|
9ad99cdcd8989905 |
|
VISUAL
wHash
|
081cfe7e7e4e0f01 |
|
VISUAL
colorHash
|
38201030000 |
|
VISUAL
cropResistant
|
38b6b619898acce0,d3db484949495933,8000806d2d800080,9ad99cdcd8989905 |
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 52 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.