Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14B23A7659209B0620B7A4FF4A87D411712D7599FF8B2B0A09D2AF7E634C3FF4AD5E108 |
|
CONTENT
ssdeep
|
768:aPtDnESGRMtRNO2HI5GPjZHqqZjispcNmzUTwCE+GnIWnIjiD99jifIxaib96Rk5:aPtDnESGRMtRNO2HI5GPjZHqqZjispcc |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b373ce8158cc8cbc |
|
VISUAL
aHash
|
e7e7c7c4476fffff |
|
VISUAL
dHash
|
8c0f9d099dd9ce36 |
|
VISUAL
wHash
|
67c7c0c0454f6fc3 |
|
VISUAL
colorHash
|
07203000040 |
|
VISUAL
cropResistant
|
8c0f9d099dd9ce36,582e371827618326,3c3c19535efd7d7d,e86233339b8d978e,0008303232100800,72cfe7e3e3642d99 |
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 437 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)