Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DC03AA30E986A8374193C1D4AF7A971B76E0F346C74307059BF8C3AC6BEAD5AED12548 |
|
CONTENT
ssdeep
|
384:PJ7r+jDZrcDT906Hc15YvhvBm7HkXGPvW+WKvk9LI+jDXbyTLsDgH:wI815Yv1Bm7EXGPu+WKvk9LxbyTLsDgH |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b333cccccc333323 |
|
VISUAL
aHash
|
cfe7c7c7ffffe7ef |
|
VISUAL
dHash
|
100d0d1c04180c1c |
|
VISUAL
wHash
|
c0c0c4c0c3c3c3c3 |
|
VISUAL
colorHash
|
07200008180 |
|
VISUAL
cropResistant
|
100d0d1c04180c1c,d5d594d4d4d6d4d0 |
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 14792 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)