Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10B332AF3111071944217DBEEF863B575B29720BC6BAF8C60E2DE5B725081BACEF48856 |
|
CONTENT
ssdeep
|
1536:Nx8wgoghH9ie5t/OyWi9oq0Ic6TEJLWiNYeGmC1dHMBzOSkqJ3rsQBGlDeBVip:N0TZ8pSSz3IIE |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ed6d92926c64929b |
|
VISUAL
aHash
|
ffcbd3d3d3efe7ff |
|
VISUAL
dHash
|
a812161616090c10 |
|
VISUAL
wHash
|
3703d3c303072333 |
|
VISUAL
colorHash
|
07007000400 |
|
VISUAL
cropResistant
|
a812161616090c10 |
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 22301 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)