Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12D73747611427A3F108382E19368D75DE382E60DC7A78946D7EC832F67D6DE0EE39264 |
|
CONTENT
ssdeep
|
1536:e7wuGdWDcevx09bwRebN37l0Kmk+rK9u09xVuz8dl:aG90C37qKmkmKnhl |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c2516c3e96d6b664 |
|
VISUAL
aHash
|
00003c7e7effd1ff |
|
VISUAL
dHash
|
ec93ccd0ccec23ce |
|
VISUAL
wHash
|
00003c7e7eff81f3 |
|
VISUAL
colorHash
|
06010000e00 |
|
VISUAL
cropResistant
|
c8c8d4cccc33671c,84abd393ccc8d4d4,4561417971690141,d325252cd0cd2d2c,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 6 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)