Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T172E2553062081E7D9617DBF0E776B73562EDC249EA1FD81CF57C02B553CAC89A823698 |
|
CONTENT
ssdeep
|
768:ZSunFPPSYqEJhaxzcQZ7+CIYfIxHXfWpfIpW:tSYqEJhaxzcQZ7+Al |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9c9c96363633b19c |
|
VISUAL
aHash
|
4638180018183c3c |
|
VISUAL
dHash
|
dc73323230325849 |
|
VISUAL
wHash
|
7e3c3c1818187e7e |
|
VISUAL
colorHash
|
38000000007 |
|
VISUAL
cropResistant
|
dc73323230325849 |
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 302 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.