Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A3E239B492309335B1C247E8DA6429287A5FE1DCD7C695B4F388AF55B0D6CE8D8260CF |
|
CONTENT
ssdeep
|
384:Y7/t2u8fTORhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsfU0RWWMd:Y7/t2u80hhPhleMeDGCSPxeeWmHJW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c0703f1f4a9f6968 |
|
VISUAL
aHash
|
8066e070f02e2f00 |
|
VISUAL
dHash
|
5ccc8aaba3ccecc1 |
|
VISUAL
wHash
|
8066e670f87e7f20 |
|
VISUAL
colorHash
|
30001008180 |
|
VISUAL
cropResistant
|
e0c4c4dcdad8e8f4,e896a92131b3c6e0,1008303232080000,5ccc8aaba3ccecc1 |
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 75 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.
Pages with identical visual appearance (based on perceptual hash)