Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17EA3DD319166CCB381DBE2E446359B1F72A6D308E9531782A7E9C39D2FCBD81CD81A17 |
|
CONTENT
ssdeep
|
768:iWClju4Su0reEsCuk+ci9NlHj+seYhX/w90DIF0yzmLbpEasDQFoQynM1Xr0uBiO:bCljuq0Yc3j4nl7 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b8c6399e8b3c8e32 |
|
VISUAL
aHash
|
ffffffffffc3c3c3 |
|
VISUAL
dHash
|
288e0e0e40169696 |
|
VISUAL
wHash
|
bfc3c3e7cb818181 |
|
VISUAL
colorHash
|
0e038040000 |
|
VISUAL
cropResistant
|
288e0e0e40169696,33472c0e2d0d5d4c |
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 46 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)