Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EEA37271B6432836207FA2CBD0171B0C52C3F38DDB428AD5A7FC83A997EAD647D65258 |
|
CONTENT
ssdeep
|
1536:BgmA2eTuEOs/B/UvnHrXpJH8HunjnxlBvhfPRTUaee2aAeu5dYMFPl/DNOdtPZfm:umA/TuEOs5M/L5xuaL7RRPRiWEf |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
aa2e64d5139d6467 |
|
VISUAL
aHash
|
ff010000ffffff00 |
|
VISUAL
dHash
|
c8272739d90032b1 |
|
VISUAL
wHash
|
ff000000ffffff00 |
|
VISUAL
colorHash
|
0e680001000 |
|
VISUAL
cropResistant
|
0049cbd989c9cb20,a2272739d9c7321a,c9c9240180012180,23332e2a3a3818d8,0c33b24d1585c590 |
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 995 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.