Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T186A1A63321002E3E25A7C7B0FAD6B759857EC74ECA6F8954F2A846E39BC3D54C853294 |
|
CONTENT
ssdeep
|
96:T6x3M8MExBx246YhlJb/kFnsi5NE7Kl/kFxK55AJEGbnPIG/:+x3tjxBxbVrMG7MT+JrAG/ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
99993333999999cc |
|
VISUAL
aHash
|
1818181818180000 |
|
VISUAL
dHash
|
b2b2b2b2b2b24c30 |
|
VISUAL
wHash
|
ff18181818180000 |
|
VISUAL
colorHash
|
000000001c0 |
|
VISUAL
cropResistant
|
a8808e2c989a80aa,aa8a8ee8a6616996,b2b2b2b2b2b24c30 |
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 193 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.
Pages with identical visual appearance (based on perceptual hash)