Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16A518B6819BCDD3306ABC1E37AB34B1B26C0D6C4DB47130147F993AC2ED2CA6DEA5145 |
|
CONTENT
ssdeep
|
24:hR/Cq9+YcwEkVHoQvRKlLiN2uT+oo6c65qKp6NzNtvonhoe2+JIHASJqLpHJT9+u:T4YUkxBEuN2uTk6v5qm6J6U09dh9VcQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cccccccccccccccc |
|
VISUAL
aHash
|
5a24180000000000 |
|
VISUAL
dHash
|
3208100000000000 |
|
VISUAL
wHash
|
3f3f333300000000 |
|
VISUAL
colorHash
|
38400038000 |
|
VISUAL
cropResistant
|
3208100000000000 |
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 48 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)