Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18F22FCB3501C9D0E6711D25AFE0EB19CC1A3594D92EDACA5F2AC0A3F11A5BB1502FE37 |
|
CONTENT
ssdeep
|
96:T9CuHnNlKYHJRB4w2+Bo+uSZLNqPHKYgg9jxzoj+d4mLufHBzqpeOrlZVQoxwNr/:NVVpLwHUjw0zqpPrlEoqH2aT7l |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f5cb9238ca74ab24 |
|
VISUAL
aHash
|
ffe2e2f0c0c2c2ff |
|
VISUAL
dHash
|
1654464626061626 |
|
VISUAL
wHash
|
ffe2e2e080c2c2f6 |
|
VISUAL
colorHash
|
06480001000 |
|
VISUAL
cropResistant
|
1654464626061626,f0e0809250642703,0e12151505090929,311111c9c9092b65 |
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 5 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)