Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13BD210D0E177077B013B81E261E9DB96E0D6D24CCA9BE400A3FD23161BCAC997C96B56 |
|
CONTENT
ssdeep
|
768:xtQvEhtQvEppjZLlCmPfo6riHRdLleM0pjZLlCmPfo6riHRdLleMZs2:1pjZLlCmPfo6riHRdLleM0pjZLlCmPfk |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cccccc3333333333 |
|
VISUAL
aHash
|
1818181818181818 |
|
VISUAL
dHash
|
b2b2b23a323a3a32 |
|
VISUAL
wHash
|
3c3c1c1c38383c3c |
|
VISUAL
colorHash
|
38000030001 |
|
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 27 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)