Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F9F2B431D08A6A3F09A763C1E3B5A35AA3D542CCE943472643FD834D4BDEC90EE079A5 |
|
CONTENT
ssdeep
|
384:YFfIIVi9IIIII9blBVRRH+JTYwF1/lVEY20Cjo6Hl1flfbpW:kfIIkIIIII3ETYU1/fZ20Cjo6+ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3e35c1c3963c69c |
|
VISUAL
aHash
|
00c1e7ef7f3c1818 |
|
VISUAL
dHash
|
8787cfcbf1e5f0f0 |
|
VISUAL
wHash
|
00c1e7ef3f7e1818 |
|
VISUAL
colorHash
|
19030000000 |
|
VISUAL
cropResistant
|
f3e3d3ca9d988c0c,000260e4cc400000,8787cfcbf1e5f0f0 |
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 38 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)