Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F8837570B22401775153CFC4972A2E52716FA37AE3E252847EEE42585EE6CFCFC82694 |
|
CONTENT
ssdeep
|
1536:cHTwr949Gj+qNxxqhaxBpLIU7iO9Yuywd5pU3qtyTd83q0ypdI3qeyudu3qgypd4:X4R |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e1ce9a65cf289a31 |
|
VISUAL
aHash
|
ffffffc3c3c3c3cf |
|
VISUAL
dHash
|
4d8e698686969696 |
|
VISUAL
wHash
|
21c3e7c3c3c3c3c3 |
|
VISUAL
colorHash
|
07402000000 |
|
VISUAL
cropResistant
|
4d8e698686969696,5373692a7bc9c860,2663e332ce8bf3f0,e3e2c0e631951ae1,7989b05c4b1b338f,2256660f8fcad0e2 |
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 5 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)