Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A7E2B5319005B53F16ABB3D1E771A35AB38687CEE943071A82FD878C5BDFD909D0A446 |
|
CONTENT
ssdeep
|
384:7b1nvIIKx9mIIIII9SlBrm+KUO+uB4Sii8l38s7aiqDEOYpUmqeTuOpW:1vIIHIIIII2uBsT7aiOCJQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3e35c1c3963c69a |
|
VISUAL
aHash
|
00e1e7e77f3c3818 |
|
VISUAL
dHash
|
8fc7cfcbd9e5e3f0 |
|
VISUAL
wHash
|
00e1e7e77f3c3818 |
|
VISUAL
colorHash
|
31030000000 |
|
VISUAL
cropResistant
|
f363d3ca8d988c8c,0000606161600000,8fc7cfcbd9e5e3f0 |
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)