Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CD42EC7460689E33579792E6B6F2DB4A3290C346CE47270093F993EC1FC6CD4DD0A5AA |
|
CONTENT
ssdeep
|
192:1XFQH+LS0cP0H9LDoAKYFpq9kD21/kCG4H+8N2:pi0SmwCKpi9 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b398cc33cccc3399 |
|
VISUAL
aHash
|
ffffe7ffe7e7ffef |
|
VISUAL
dHash
|
00304812484c3008 |
|
VISUAL
wHash
|
0c0c242c3f27273f |
|
VISUAL
colorHash
|
07038000000 |
|
VISUAL
cropResistant
|
00304812484c3008 |
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 25 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.