Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E36241306244897EA093C3D9F772373F22AAD295E607434896EDC7285ECAC59EC336D4 |
|
CONTENT
ssdeep
|
192:fEG/NyNtRgLgddQwiWbYik3uHnrneqEj/SYWFC0vkCyFHxGC:f9/qQwiWbYikeTeqEj/SYWFC0vpyp0C |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b166c691c6c69b9a |
|
VISUAL
aHash
|
f7c3c3c3cfcfcfff |
|
VISUAL
dHash
|
0e0f9e969e9d9d9a |
|
VISUAL
wHash
|
c38181c3c3c7c7cf |
|
VISUAL
colorHash
|
06000000180 |
|
VISUAL
cropResistant
|
0e0f9e969e9d9d9a,8b090b8f8f36361f,bf9f7f3fbfbfbfff,176944b1d1696117 |
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 30 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.