Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T118448A234159792A4437C6D024A99B7AD5B6DE4BFAA70A000FECC7F73AF9C50741B22D |
|
CONTENT
ssdeep
|
1536:531RRhFyVjvL7rNXCuaEKqDqrEMqNPRs5UgQmTa3MZo+Hd1+T0lIwWG84wusA+63:POQ9rfQ134YNK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e852c29e166eb6b2 |
|
VISUAL
aHash
|
00000000ffffffff |
|
VISUAL
dHash
|
a8d183331c33271c |
|
VISUAL
wHash
|
00000000ffffffff |
|
VISUAL
colorHash
|
06010000e00 |
|
VISUAL
cropResistant
|
21929094d5d29090,a46565baa2535340,333773c2988d2b23,38789d9c8c8c8d8f,82909a96968eb082,8c003a3727300e0e,8ca8e9d182283394 |
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 31 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)