Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12C02A6223050593F1A27CE91F2E4F147974EF21DC56794B8F5DA11AF36E2EE0C663A22 |
|
CONTENT
ssdeep
|
96:TGaL6rG7G7b7e2P9+yCwG5PjyxLYjYub6C7sCA2EQTQ883rcBQM883rOLYjpXk:aaGrxP6Y9Yp7hA2DQXriXwYF0 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b323cccc99333366 |
|
VISUAL
aHash
|
ffe7e7efffe7e7ff |
|
VISUAL
dHash
|
100c4c1a300c0c30 |
|
VISUAL
wHash
|
cbc3c3cbd8c0f8e0 |
|
VISUAL
colorHash
|
071c0000000 |
|
VISUAL
cropResistant
|
100c4c1a300c0c30 |
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 20 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)