Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13981C025200175B7C617B9497AA25F0921739288DEEBD1D827FC4F4917E3EAC8C1E985 |
|
CONTENT
ssdeep
|
96:djSzOJxqAt4xvSvOayjLJXpdJJKeZNiJvF8G:djSzAxFt4x6WaULJXpdzk |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ce3331cc3398cc67 |
|
VISUAL
aHash
|
0000383c30381000 |
|
VISUAL
dHash
|
006064606060a000 |
|
VISUAL
wHash
|
003c3c3c3c3c3c30 |
|
VISUAL
colorHash
|
38403000000 |
|
VISUAL
cropResistant
|
a3223831316a387a,923ca4a8e2beb666,006064606060a000 |
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 26 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)