Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A914BD2C701105B72537A6D9FC6ABF49B3A2F74FC55EC5485AEC82680FCBDA2B858071 |
|
CONTENT
ssdeep
|
1536:gVywCsjzbnj1yYCt2n+EdZitV+hROsNOxMl2Nosomyp/FuIoedl4oX6AsbFXGhQS:ICNw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3b0b37d65064a46 |
|
VISUAL
aHash
|
ffeffff7c0000000 |
|
VISUAL
dHash
|
1a1aed2c12185555 |
|
VISUAL
wHash
|
ffffffb780002000 |
|
VISUAL
colorHash
|
02011000240 |
|
VISUAL
cropResistant
|
f0c6b2a9a9aaccf0,92a62647172e92a2,343a6525ca841153,22232f3329392496,dcc68480cc8c96d6,1a1aed2c12185555 |
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 55 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.