Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T160E1E5F69220875E9082D5ACFF22F0D0C24ED09FE656DAD0D7AE87B804D7CD8F566990 |
|
CONTENT
ssdeep
|
192:a/bhEHhnmh3s3TdN8gOreijywAcQSyUZxBcFL/W:MNEBnc+ggOX2NjaNcFK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e8607059593bf6a6 |
|
VISUAL
aHash
|
0000ffffffffbfdf |
|
VISUAL
dHash
|
838786b2f2475775 |
|
VISUAL
wHash
|
0000e7ffffff8100 |
|
VISUAL
colorHash
|
0e180008000 |
|
VISUAL
cropResistant
|
869632f290477775,6083939383608084,23230515a5b73b1a,aaaaeb696d2d2d16,73535b4b4b597962,a6a7a5adadada632 |
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 14 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)