Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DE137F51A0895337023BA0D6E9E61FB661D1012EDA27A61297FD07AD7BEFC007847E1F |
|
CONTENT
ssdeep
|
768:JGmI+nYnnY9SbQP4rCtsVXF+SWwd6pasYgWMWrWmWP7x7hd7G7zOlZ:sR+nYnnY9SbQP4rCtsVXF+SWwdqZY+D |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ea9c07e670865dc3 |
|
VISUAL
aHash
|
ffff9fddc9912100 |
|
VISUAL
dHash
|
b03333313963c1c1 |
|
VISUAL
wHash
|
ffff9f9dc1810000 |
|
VISUAL
colorHash
|
00400180000 |
|
VISUAL
cropResistant
|
b0333b31393363c9,d1c8f9bcf27e6e0f,27192890988c86a3,2b3339393361c9c1 |
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 141 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.