Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19FD2B5366445647F170348D1B2B07B8E71CA824ECE130C88F6F8839E6FEBDA5DD256A4 |
|
CONTENT
ssdeep
|
384:k2RiUWzMpUQ7kgHN1R6JahZC9QnumCN7cJFabs4iLKah/6wloHifCyN3:k2RJR7kgHN1LAQn9LKO3 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d82de75e88d16325 |
|
VISUAL
aHash
|
ffa3e3491dbcfcff |
|
VISUAL
dHash
|
31264b93b1648422 |
|
VISUAL
wHash
|
bf8301090c1cfcff |
|
VISUAL
colorHash
|
06200030000 |
|
VISUAL
cropResistant
|
31264b93b1648422,3347881a1c58b6a7,244b870f3f3d7bff,d0c37819072e138e |
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 294918 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.