Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17252A63190091C3BD103C185A351E3EF21A6A293DB0B0E04D6F853BAE6EAD91DD7B6DD |
|
CONTENT
ssdeep
|
384:m8iNIilFNb/T7A0NLpT7A0NBT5A0NNT8A0N9T7A0NAIoBDjF1EkJk4ZkZE410z+L:TU5Wyzkz5 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
96b2694bc66db096 |
|
VISUAL
aHash
|
0d0e1e3e3e1e1800 |
|
VISUAL
dHash
|
d9bcfcecec7c7273 |
|
VISUAL
wHash
|
0d0f3f3f3e3e3800 |
|
VISUAL
colorHash
|
32e80000000 |
|
VISUAL
cropResistant
|
6667e0b49498c8c0,92beb8b2b28eb2a2,2828d6d6962b6bd9,d9bcfcecec7c7273 |
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 48 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)