Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F2629576EC52385BA10155A4F2F24FDDA08FA10BD317DC60F3E42BA399CACF588992D5 |
|
CONTENT
ssdeep
|
96:va1lYSr8QvQKuiJeSMzAdyNc7JHrGPPbkcxz2PTeiwDsK73Mr/x/BDXgtHnPJ8Fy:lqFuKaMvnA14EKfX2QWS3Sam |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
88d077abaa5755a8 |
|
VISUAL
aHash
|
00405c1d19000000 |
|
VISUAL
dHash
|
508bb075b3320810 |
|
VISUAL
wHash
|
0040fc1f1d701c1c |
|
VISUAL
colorHash
|
07038000000 |
|
VISUAL
cropResistant
|
6e2c6fc6d7d380a0,a2b2e28b17baa6a2,508bb075b3320810 |
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 33 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.