Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BFE240308401663B0A8357C4A6319F9AA3C2D344CA2B474D67F9C76D6FCFD91CCAA2E4 |
|
CONTENT
ssdeep
|
384:+RGVaU5Vo2Fq0E/C5CeYDlgPukIkKkKXOKQKFiPcO:1TG/5CIkBmONiO |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
91e56c3c9ce09b1d |
|
VISUAL
aHash
|
00006c7e1e0c4000 |
|
VISUAL
dHash
|
36cad8d89898b873 |
|
VISUAL
wHash
|
026e7efe5e1ec801 |
|
VISUAL
colorHash
|
30001600010 |
|
VISUAL
cropResistant
|
e8ccae1f27b6cef0,36cad8d89898b873 |
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 19 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.