Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BFE1F7EB5220875E5592D8ACFF63F090824ED09FE6A2DAD0E69E877404E3CD4F527840 |
|
CONTENT
ssdeep
|
192:a3Q5mXzdNU3P6+2tm2OwDjywAcQSyUZxBcFL/W:CtmG2NjaNcFK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e86078595939f5a6 |
|
VISUAL
aHash
|
0000ffffffffbfdf |
|
VISUAL
dHash
|
838786b2e24f5735 |
|
VISUAL
wHash
|
0000e7ffffff8100 |
|
VISUAL
colorHash
|
0e180008000 |
|
VISUAL
cropResistant
|
a68633f2cc577775,608393939300a082,9dd55454757636b2,494be7e7a7a7261a,6565662a2a2a6266,aaaececdad2d3517,9859416262666614,e96d569694d6cecc,e2e2cacadada9a98,254545697814968b,d64ece96b69199a9 |
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)