Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10361A5305228DF3B058A83D8E7706B3F32AB9189C24E071596EC83B85AE5CD4FE23194 |
|
CONTENT
ssdeep
|
48:Te4K3X6q0cLsXAStVpC7rgo72kPQXc3PiGLqwq+5Jt/l3otw:Te45IwQStAgodPQs/ilw95PKtw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc7333cc9933cc26 |
|
VISUAL
aHash
|
0000181818180000 |
|
VISUAL
dHash
|
0810303232320911 |
|
VISUAL
wHash
|
c0903fff1818ff03 |
|
VISUAL
colorHash
|
38008200030 |
|
VISUAL
cropResistant
|
0810303232320911 |
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 21 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.