Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E5F2C632D05A693F05ABA3E1A770A32AB3D543CED6430B2942FDC35D5BDBDD0AD064A4 |
|
CONTENT
ssdeep
|
384:pxisII1iIIIII9IlBYYeOyCH+JT5Nv2lvgrajCrpCodEAqQPfWpW:XisIIIIIIIIrOyCET5NvEgraercCqQnx |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
86e3711c9c397396 |
|
VISUAL
aHash
|
00e1f7ff7f181818 |
|
VISUAL
dHash
|
87cfcbf3e5f1f0f0 |
|
VISUAL
wHash
|
00f1ffdf7f181810 |
|
VISUAL
colorHash
|
19038000000 |
|
VISUAL
cropResistant
|
f363d3cadd988c8c,0002c8fcd4440000,87cfcbf3e5f1f0f0 |
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)