Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11B1222283558897B17736BC2BAE1ED6A68D1B34FC60586B4C0FB53ED46D0FD18C64827 |
|
CONTENT
ssdeep
|
96:TMGsgOm66Ner+l6P+nAmVPbFItHy5mz4xo7Lynx1EIUDA89XehvF:LD+RwbPbFIxyZC/ynx1E/DA89Xe1F |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e5c31e38270c339f |
|
VISUAL
aHash
|
e0f0f0e0e3c31b03 |
|
VISUAL
dHash
|
074042868696b63e |
|
VISUAL
wHash
|
e0f8f0e0e3c71f03 |
|
VISUAL
colorHash
|
30000000c10 |
|
VISUAL
cropResistant
|
074042868696b63e |
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 108 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer scans for high-value tokens (USDT, USDC, SOL, memecoins) and prioritizes draining based on USD value. Low-value tokens are ignored to optimize transaction costs.
| ID | Português | Inglês | Trigger |
|---|---|---|---|