Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11DF113E1C044DC3B531385E5B7F5275FB596C359CF020E8853F892AA5BDEC60CA23A9A |
|
CONTENT
ssdeep
|
96:Tkfy7khOlzH0XfeGnVY8yEFwvFYetXSHF5e9Xyz/Jo8VYYhQPJ:Qfy7khOlzH0X1n7yEcsmsz683hQR |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3834343babc6cbc |
|
VISUAL
aHash
|
0000ffffff000000 |
|
VISUAL
dHash
|
dccd32000aa30800 |
|
VISUAL
wHash
|
347cffffff000000 |
|
VISUAL
colorHash
|
03000000007 |
|
VISUAL
cropResistant
|
f0d4aa8e698ecce8,4667a94b5a984b4e,4020303030280830,2448d8d4c9ccc42a,a2a3188200000000 |
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 63 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)