Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14B9232B421601BAF8987DEF53268E73D9294C7CCCE77CB0BB3E4A25617A6DC27901251 |
|
CONTENT
ssdeep
|
384:IiGL+X6LN7BpqNgarFazhxHkusaO+6OtPR3eJn+UKXnTJ:IiM+X6LN7PcrFa7kusaO+6OtPR3eJn+X |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a4da94b5e1297966 |
|
VISUAL
aHash
|
173f012323131303 |
|
VISUAL
dHash
|
f66567c3c7666fe6 |
|
VISUAL
wHash
|
3f3f016b27171703 |
|
VISUAL
colorHash
|
00001000180 |
|
VISUAL
cropResistant
|
cdece4e6afcacace,fcf128202c301434,dfcfcd4d4d6d69f3,ec8af3cd8ce4e80e,1c3ee4e426e664e5,cf899898828387e4,f66567c3c7666fe6 |
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 7 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)