Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F5339930A9C2A8374193C1D49F7A971B76E0F346C7434705ABF8C3AC6BEAD5AED06548 |
|
CONTENT
ssdeep
|
1536:rODzYYZ5gmREcoAljRX9xozE+BIY6JyELsDgH:rORyS |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b333cccccc333323 |
|
VISUAL
aHash
|
cfe7c7c7ffffe7ef |
|
VISUAL
dHash
|
104d4d0c14180c1c |
|
VISUAL
wHash
|
c0c0c4c003030303 |
|
VISUAL
colorHash
|
07000018080 |
|
VISUAL
cropResistant
|
104d4d0c14180c1c,143494c4d49496d7 |
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 16457 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)