Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12F7369312906AC6B66F385C1F409BF05EA7EE30A809CC6F7559CC14B5EC7CA273AA4D5 |
|
CONTENT
ssdeep
|
1536:v0HiBtMZeFFxs+5wYm9wmp7tqui92CoAdkhicpklbIR+y+f7o6kAToci+2PYC3GU:J8 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e82020c9d67f5b5e |
|
VISUAL
aHash
|
434300c0ffff80c0 |
|
VISUAL
dHash
|
86861d8cb1b329a9 |
|
VISUAL
wHash
|
434300c0ffffc0f5 |
|
VISUAL
colorHash
|
02008000c00 |
|
VISUAL
cropResistant
|
a280801a3a80a0a2,a292642d1b338ca2,323b692dcd8d3557,c061319392732b18,c1e19182c3c24061,8986968e6d9f1f9f,327309ba880c2da9 |
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 84 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.