Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T101832AB43A59FA665AF3439310DF1103B378152B580E4D206350FD9EB6BCC9BA067F9A |
|
CONTENT
ssdeep
|
1536:8qEuTVq53QSoHxh8N6MmbXhjaPnQsR+96mujHjKp:8+TjzmN6/btZ96/HjM |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e3f17c38186cc783 |
|
VISUAL
aHash
|
c0e8ecf0ece10000 |
|
VISUAL
dHash
|
0308c8c0c9a98381 |
|
VISUAL
wHash
|
c0e8ecf8fdf1e100 |
|
VISUAL
colorHash
|
38000c00008 |
|
VISUAL
cropResistant
|
0308c8c0c9a98381 |
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 640 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)