Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18C2373719311092F535305D8F1A1F769919E6349CF2B991DB3AC12B23BCACB99CEB0D8 |
|
CONTENT
ssdeep
|
768:0pcxMnZ38uIwrZ8HPP4qPNLqPNYPzPLCo7LqPQm86jPS5e6Pd0PE48HPP4qPNLq5:k8pwrOX4qboRjmCcX4qboRjmCRpdZYy |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
95e93c86d694897c |
|
VISUAL
aHash
|
1800fffffe3f0000 |
|
VISUAL
dHash
|
629ff2f070f07cf8 |
|
VISUAL
wHash
|
1a00fffffe3f0000 |
|
VISUAL
colorHash
|
0100a000280 |
|
VISUAL
cropResistant
|
62cf32f0f474f17c,f1c3747cfccc78f0 |
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 351 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)