Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16BE106F69220865E9082C1ACFF22F0C0D28ED09FE662DAD0D7AE87B504D7CD8F467940 |
|
CONTENT
ssdeep
|
192:aLxpV/hhVOhDU38dH0uOdvjywAcQSyUZxBcFL/W:MPVphVUZJbOF2NjaNcFK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e8607859593bf4a6 |
|
VISUAL
aHash
|
0000ffffffffbfdf |
|
VISUAL
dHash
|
838786b2e2475735 |
|
VISUAL
wHash
|
0000e7ffffff8100 |
|
VISUAL
colorHash
|
0e180008000 |
|
VISUAL
cropResistant
|
868633e3c8577775,608393939300a080,8d5555557577361a,594be7e7a7a5251a,6565642e2a2a6266,aaaaeec9a9291517,9899516266666414,e9e9749494d4cecc,62624a4a5a5a1894,a54545697414968b,d64eced6b69199a9 |
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)