Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E48163775020085F5A2B4918FBC6F944915AC386C27E9DB6F2DE12ED2AE0DB0DDBB130 |
|
CONTENT
ssdeep
|
96:TsxAvhSYAmeOEnTjAJEtZ0pzR1KHfd3Ghnr2/:gflyK13G8/ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8db367c32236dc8c |
|
VISUAL
aHash
|
0118181818181800 |
|
VISUAL
dHash
|
ce7232b2b2b233c6 |
|
VISUAL
wHash
|
ffbf9b1b1b181800 |
|
VISUAL
colorHash
|
06039000000 |
|
VISUAL
cropResistant
|
96968e8ea2aa33aa,ce7232b2b2b233c6 |
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 8 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)