Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BDF1B673A0100837153B87D8EBD0BE587123A35EE5066858EBC844E58DC3EF9E997772 |
|
CONTENT
ssdeep
|
192:6nVRfWwV1Mr6zUgC/N+zZgWW4dxOHnzFcWE4e:k6rjgC1+P3dIHnzFch4e |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8ccc3233d9327799 |
|
VISUAL
aHash
|
1818181818000000 |
|
VISUAL
dHash
|
303030b2b2013100 |
|
VISUAL
wHash
|
3c3c3c3c3c010100 |
|
VISUAL
colorHash
|
38000038000 |
|
VISUAL
cropResistant
|
0008303232100800,303030b2b2013100 |
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 24 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.