Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A2C2E875E114633A932B8BC4FAA06B1F71AB124CE5531CA8E3FC47D11FC2ED8D822965 |
|
CONTENT
ssdeep
|
384:8DlmJvxIhjYnKPqVoECU9a86lSwVBLCELWJNFkf/kAnvxJIISQ3:1vnf/a86lSwyNFexGISQ3 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
82b17dd582aa45f5 |
|
VISUAL
aHash
|
ff00007f7e708100 |
|
VISUAL
dHash
|
8e0400d5d4cc2b23 |
|
VISUAL
wHash
|
ff00007f7f74c330 |
|
VISUAL
colorHash
|
38000000e00 |
|
VISUAL
cropResistant
|
8e0400d5d4cc2b23 |
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 302 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.