Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EF81102190101D3FD53A5AA87DC3E60898F3E1D9DE490040A5EA518C9BDFF51AB3FE76 |
|
CONTENT
ssdeep
|
96:zsuCFKHbzyO9ULNSaeWLOVJFawkLvlA0PZ:Ocbz19+mzuAU |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9999666699996666 |
|
VISUAL
aHash
|
0000181818000000 |
|
VISUAL
dHash
|
100c32b2b2200810 |
|
VISUAL
wHash
|
0c0c3c3c3c3c0000 |
|
VISUAL
colorHash
|
00007000000 |
|
VISUAL
cropResistant
|
cc8ea2c0e2c03171,100c32b2b2200810 |
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 389 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)