Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15253BC30B8C6A9374183D1D49F7A971B76E0F306D6430705DBF8C3A86ADED9AED4A508 |
|
CONTENT
ssdeep
|
1536:wcNko8yhWllaGwtqOXGmFWtc1PIEkek5K/k6VpDoOUnUR/3QH:wcNXzmuEnUg |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b333cccc8c333333 |
|
VISUAL
aHash
|
cfe7c7c7ffffe7e7 |
|
VISUAL
dHash
|
104d0d0c14180c0c |
|
VISUAL
wHash
|
03030703c3c3c3c3 |
|
VISUAL
colorHash
|
07000030080 |
|
VISUAL
cropResistant
|
104d0d0c14180c0c,406969292d2cf44c |
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 14133 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)