Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18D150B78832C93BC5547C7ECDB7AB0A8131EB0EDF27A4194651C45B06693ADDE86F9C0 |
|
CONTENT
ssdeep
|
12288:fAtTg90M37heoHrcwVOBhBxf1Whbv1ifUQjQyQ:6Tg1/HrtV8hBxN20UQjQyQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d25e959455d5c552 |
|
VISUAL
aHash
|
3e04f878747f7f00 |
|
VISUAL
dHash
|
b8bdd1808dc0c0c0 |
|
VISUAL
wHash
|
3e0468637c7f7f00 |
|
VISUAL
colorHash
|
07000008601 |
|
VISUAL
cropResistant
|
b8bdd1808dc0c0c0 |
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 1601 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.