Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12F43A5642244093E75538AE8F2E5B73DE1BEC6CAC62B484CB7AE01A733C7C589D57394 |
|
CONTENT
ssdeep
|
768:Iv//tjW3TYCYCYa4p25/uE6E1SMsvwUG0lIdcBnE8u0VQR5lsHIA5xk7b:IH/Uf8lIdcBnE8u078 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8eb0a0e2dbc8f5e4 |
|
VISUAL
aHash
|
ff3fbf3c38000000 |
|
VISUAL
dHash
|
cdede86868606564 |
|
VISUAL
wHash
|
ff7fff3c38300000 |
|
VISUAL
colorHash
|
0a000c00000 |
|
VISUAL
cropResistant
|
636397cdcdededfd,0e0e8e1ad24f4747,1637a58d56945616,cdec686861606566 |
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 8 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.