Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11303A76C21414FBF6937976262617A28B0B4979DCF6B464CF3FA62817BD2D44CED8038 |
|
CONTENT
ssdeep
|
768:mkPG4kWg/+CT4C3iAH+DCvkWg/+CT4C3fCV1KCU0:43n4CSAer3n4Cs1KCU0 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
dade663125258733 |
|
VISUAL
aHash
|
003c3c3c1818003c |
|
VISUAL
dHash
|
b07179f0f0f0d460 |
|
VISUAL
wHash
|
5efc3c3c3c7c003c |
|
VISUAL
colorHash
|
300000001c0 |
|
VISUAL
cropResistant
|
a6b5797a5a6125be,d35329a929284c4f,26261aba2a9adadd,cc4e4a49094ba9b9,b07179f0f0f0d460 |
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 1084 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer supports multiple blockchain networks and checks for high-value tokens on each chain before executing drain operations.
Pages with identical visual appearance (based on perceptual hash)