Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F7D211D0E173077B013B81D661E9DB96E0D6D34CCAABE440A3FD23161BCAC997C96B61 |
|
CONTENT
ssdeep
|
768:ztQvEhtQvEp/hvkX0kOFcw5gkU9qvaIO/hvkX0kOFcw5gkU9qvaIZs2:X/hsX0kOFcw5gkU9qvaIO/hsX0kOFcw5 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cccccc3333333333 |
|
VISUAL
aHash
|
1818181818181818 |
|
VISUAL
dHash
|
b2b2b23a323a3a32 |
|
VISUAL
wHash
|
38383c3c38383838 |
|
VISUAL
colorHash
|
38000030002 |
|
VISUAL
cropResistant
|
d010521353329149,b2b2b23a323a3a32 |
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 7 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)