Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A972F976B21C3370490343EBAB6A22FEB613527DC7515BACD768811472568FC8B72EC6 |
|
CONTENT
ssdeep
|
384:Q6oCEPS6u3/AT6WMXe8N8K0/lqsmMpBZ7eg/B:bohqtM6Wg6tm4/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
972a55aa552ad5aa |
|
VISUAL
aHash
|
070f5d7f3f3f25fe |
|
VISUAL
dHash
|
0e9dc1c1f465c9c2 |
|
VISUAL
wHash
|
07030d333f0717fe |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
0e9dc1c1f465c9c2 |
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 485 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.