Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17CC1B5636308580C3227E168FD62B74D972A822FE6192A5476E011DFD5DFAF0C17B365 |
|
CONTENT
ssdeep
|
48:sadbBjq7FqLGMRjWYMRjWjwjggrfSPMlNaNrN1WqC/9QqOsmdR9UN9j4jBYu+jI0:s8hpWxp6YVGiqAVOskOC1YRA7zwKPeFF |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d4d4f1d1d4d4d0d1 |
|
VISUAL
aHash
|
ff00001818000000 |
|
VISUAL
dHash
|
c070e0f0f0e0e0e0 |
|
VISUAL
wHash
|
ff383c3c3c3c1c18 |
|
VISUAL
colorHash
|
38000038000 |
|
VISUAL
cropResistant
|
0000808000c0c000,c070e0f0f0e0e0e0 |
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 3444 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.