Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1673101BDA15159EF12039EF2B2917E1DB0C5D70BCEB75C08B1AE02A773F2E415C52164 |
|
CONTENT
ssdeep
|
48:T31ZdUvjP3/uJdPeNU082aaCA2ZvNNdEVvB:TfdU7iwU05yZGRB |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b139cec633189cc7 |
|
VISUAL
aHash
|
ffcfcfc7c7cfffff |
|
VISUAL
dHash
|
6498969e9e9c1860 |
|
VISUAL
wHash
|
cfc7c3c7c0c0c0f0 |
|
VISUAL
colorHash
|
07242000000 |
|
VISUAL
cropResistant
|
6498969e9e9c1860,ddcdd25b59b6e7c2 |
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 22 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)