Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12F3219F8722414E1DE0397CAB922327AA043927EDE9356D8D369875476D9CFDCC40DC6 |
|
CONTENT
ssdeep
|
192:QoRoBZJ5I9H59ZoMu9cuGRmKbMpBXp7sfgg8gk:QqoWHfZnsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bf1ac06ac5b03d2d |
|
VISUAL
aHash
|
fd9d0f0f0101efff |
|
VISUAL
dHash
|
79717b7d536f1d86 |
|
VISUAL
wHash
|
891d0f0f0101efff |
|
VISUAL
colorHash
|
07600010200 |
|
VISUAL
cropResistant
|
79717b7d536f1d86,0000303030100810,fcf1fdfdd7dbcabc,2b452198c465514b |
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 487 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.