Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15FF242729085753B11A7D1D0EB3CBB1BA3C292CAD95ED1C063FC835C9FCAE91D852926 |
|
CONTENT
ssdeep
|
192:6q7EnujwD0RoBBrZEhfnMLo0BsMcmFxIWQmD8rb3y9D1nK+7jKkMOZo2OFmVDIC6:6vuj4AsEvMLZBimTz11tiCoV2Ik9tTUl |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9919131c3ee6e2e6 |
|
VISUAL
aHash
|
0f0fff1f0fffffff |
|
VISUAL
dHash
|
7d7488703480f0d0 |
|
VISUAL
wHash
|
050f2f0f0f0f0f2f |
|
VISUAL
colorHash
|
07040000006 |
|
VISUAL
cropResistant
|
7d7488703480f0d0,c591c5c181812dad,0020067171200c10 |
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 12 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)