Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F5938560C2A5563701F681D8B5A5CBB633D00188DE550F585EBD8776BFCEEA6AC0318F |
|
CONTENT
ssdeep
|
768:lNTFXmAVnRHZeZ4t10eCVoT0oTf7NY7NSGpFYXcda5M0eCxRd9t1VMVg3KePWnNf:rr0eCV52N6NSG6maq0eCxQG3lP27Gpc7 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9a9bc7c69a386561 |
|
VISUAL
aHash
|
3c3c001c1c000000 |
|
VISUAL
dHash
|
69695971690f1703 |
|
VISUAL
wHash
|
bc3c7cfcbd818181 |
|
VISUAL
colorHash
|
19238000000 |
|
VISUAL
cropResistant
|
8083bab08c8c8890,69695971690f1703 |
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 55 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)