Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T114426914BA6508AE1177C7C1E4A22E5630EBF3AFC19661967DEC5131AFCB8F1B840939 |
|
CONTENT
ssdeep
|
96:CCzhG4T1hqA9OEOWyF3r3z59G6/iB9GjH4UGrah+k1skuJ+RPoER:jR1xXtyu9UDEwPoi |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b2181c767e1c36b6 |
|
VISUAL
aHash
|
004cffffe7e7ffff |
|
VISUAL
dHash
|
3b1410b00c4d0408 |
|
VISUAL
wHash
|
00df00e4e7e700ff |
|
VISUAL
colorHash
|
07000000c40 |
|
VISUAL
cropResistant
|
00232b3b2b230022,3090300c0c0c0c00,0008517151500000 |
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 6 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.