Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15EE2B632D019A93F169BB3E1A770A36A7386838ED943171A42FDC74D0BEFD90DD1A494 |
|
CONTENT
ssdeep
|
384:py+JII1xIIIII9nlBYY33y7TwglKgERaCrgCQLFEVqQPfWpW:s+JII7IIIIIj3y7TwRgER5rzzqQnx |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
86e3711c9c397396 |
|
VISUAL
aHash
|
00e3ffff7f181818 |
|
VISUAL
dHash
|
8fcfcbf3e5f1f0f0 |
|
VISUAL
wHash
|
00f1ffdf7f181810 |
|
VISUAL
colorHash
|
19038000000 |
|
VISUAL
cropResistant
|
f363d3cadd988c8c,0002c8fcd4440000,8fcfcbf3e5f1f0f0 |
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 37 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)