Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B3E229B4A230D335B1C24BE8DA642528765FE1DCD7C695B4E388AF51B0D6CE8D9260CB |
|
CONTENT
ssdeep
|
384:Y7fUWegukT5RhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3Ass+RWuMd:Y7fUWegushhPhleMeDGCSPxeeWmHfW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c33d3ccf68b14b48 |
|
VISUAL
aHash
|
00266060f0747670 |
|
VISUAL
dHash
|
1c5cdac3c3cccc81 |
|
VISUAL
wHash
|
80266670f0f6fef0 |
|
VISUAL
colorHash
|
380003c0000 |
|
VISUAL
cropResistant
|
c2c9b9b1b4ece4e4,0010323232300800,1c5cdac3c3cccc81 |
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 73 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.