Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12F12BE342001156B23731BC97CE3E7CA60DBE30FCA4B97116AE843861FD7DA4A975B65 |
|
CONTENT
ssdeep
|
192:CD5U9TdUqBgISRo/C+7mZO0c8ezy9yEbPHOmR:CD5U9OWDNmZO0dyEbmmR |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8c4cf33399137726 |
|
VISUAL
aHash
|
0010101819ffffff |
|
VISUAL
dHash
|
10b13233310c1100 |
|
VISUAL
wHash
|
0010181819ffffff |
|
VISUAL
colorHash
|
300000001c0 |
|
VISUAL
cropResistant
|
10b13233310c1100 |
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 83 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.