Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CB72C0F5208A583702AB95C36076DF1731EAF30ADA4B424B66FC57F557CACACF80950A |
|
CONTENT
ssdeep
|
192:AOk6HqhN7bFhDZBC7E05jdB1b4QYIowm3R8P1O0gRGTfb+Hd:APhNdhmj+Hd |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3972c3cb1c71cc3 |
|
VISUAL
aHash
|
062c7c6e6c007020 |
|
VISUAL
dHash
|
d4c8c8c8d822c4c8 |
|
VISUAL
wHash
|
660e7e7e6e00707c |
|
VISUAL
colorHash
|
38002000e00 |
|
VISUAL
cropResistant
|
d4c8c8c8d822c4c8 |
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 31 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)