Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T157E2E9BD5140938EE8B7C94BAE3137906012A2BFEB764584FE6E3115FD87C88F6D8590 |
|
CONTENT
ssdeep
|
768:d6iLBIaPD2JVv6SnR3ZTmq4eU8qOe49GY9ZZ:d3LBU/v6+0Nl8P |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b6be9c3ca242c9c3 |
|
VISUAL
aHash
|
9fffffe7e70000ff |
|
VISUAL
dHash
|
2b2a080c08118a00 |
|
VISUAL
wHash
|
8583e7e7e70000ff |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
293608080c0c000b,0000000000000000,4080909696908000 |
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 5 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.