Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1417334326445DD6B04DB96C49271171A22B5E384E603028BFFF487AA5FDFEA9CE33425 |
|
CONTENT
ssdeep
|
1536:/JsIxcArd+CK1dkCnj1CRmH4RMQmq8j1HRmH4R/n7RHRmH4RVpH4Rz528kj1CRm8:hAAIDkCnj1CRmH4RMQmq8j1HRmH4R/n2 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b34bb440b8b6c5e3 |
|
VISUAL
aHash
|
ff0020846020c7c7 |
|
VISUAL
dHash
|
4c4c484dc9cc2c2e |
|
VISUAL
wHash
|
ff20ac8460e0cfcf |
|
VISUAL
colorHash
|
17606000000 |
|
VISUAL
cropResistant
|
0c0c0008000c0008,000204020244268e,9e8489a1c18997b8,a5a1a0a427243434,2802000000000000,4c48484dcbcc2c2e |
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 91 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.