Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16AE2A331A009A93F06D7A3D1EB75A76B7391838DC987076A82FCC7484FEBD90DD16490 |
|
CONTENT
ssdeep
|
384:SVIItkS0QhIIIII9FlBHMBhP21mUsBEJL/vMIsNXC1gFye5Ak4pGpW:mIItkchIIIII0JuEBw72NXqgce6k4pB |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c7e3711c9c396386 |
|
VISUAL
aHash
|
00e3e7ff7f181810 |
|
VISUAL
dHash
|
8fc7cbf3e5f3f0f0 |
|
VISUAL
wHash
|
00e3ffdf7f181810 |
|
VISUAL
colorHash
|
19030000000 |
|
VISUAL
cropResistant
|
f3e3d3ca9d888c8c,0000706969000000,8fc7cbf3e5f3f0f0 |
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)