Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D754CD234259392B0437C2E520A95B3BD1AADD4BFAE70A414EDCD7F727FAC90741B258 |
|
CONTENT
ssdeep
|
1536:kBQw1kcAvR9tMbXlOJi55R+Ovb0kov20BtPRrH8ArXvUd0gAK6Fyg0edm4vKZlpj:VrMw9kd0PRD9kNedmYKRGI1Bt |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c6506c3e96d6b664 |
|
VISUAL
aHash
|
00003c7e7effd1ff |
|
VISUAL
dHash
|
ec93ccd0ccec23cc |
|
VISUAL
wHash
|
00003c7e7eff81f3 |
|
VISUAL
colorHash
|
06010000e00 |
|
VISUAL
cropResistant
|
c8c8d4cccc332718,84ebd393ccc8d4d4,4561417971690141,4935252cd0cd2d2c,82454d7171454500 |
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 37 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)