Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19763C86AF525E83FE66AC2DDD4858811337D42AFF884C6B0A264EF5F65345C3181FB88 |
|
CONTENT
ssdeep
|
768:B+dVmYjtYjhYjWYjAYj2vs9hg8+gwxhejP4fqE/0VWv+M4yTMHeIv6RGz4gKCoUX:PQg85IcwCEtWyTDJtQr |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cccccc6666663333 |
|
VISUAL
aHash
|
1818180000000000 |
|
VISUAL
dHash
|
34b2300800000000 |
|
VISUAL
wHash
|
3f3f3f3f00000000 |
|
VISUAL
colorHash
|
38000000180 |
|
VISUAL
cropResistant
|
8200324e4c4a2a12,34b2300800000000 |
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 1685 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)