Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F7E3A8B1D175493706BFB7E4F429672E6397C3CACB9147F282E19B840B86D54A833C98 |
|
CONTENT
ssdeep
|
1536:8MaBVNzmcjwZMPYxSvRPJcoxuSlku7K3G82Szfw4ffwY/qPOGPChpDy8eyyBfraE:8oDcN00Xt |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b9394e4e134e4b39 |
|
VISUAL
aHash
|
00cfc9cfcfffffff |
|
VISUAL
dHash
|
691a9b9a9a132372 |
|
VISUAL
wHash
|
004a484a4b097f3f |
|
VISUAL
colorHash
|
07000200180 |
|
VISUAL
cropResistant
|
691a9b9a9a132372,0669496979694906,c961e9e0e0969ecc |
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 37 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)