Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10FF2D83693891D3D630786A4F6A2733D92BDC29BEA27855CF6BC016113C6D4CDB23AD4 |
|
CONTENT
ssdeep
|
768:1oqo5jFDbYr/1vDaOQkkCB3vWIoAqm0QCoJyvZZyZlMTSvrOylvcVTFPObZtq/9F:1ruOQkkdCOeCO4/ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d9a6e098e6c9c6ca |
|
VISUAL
aHash
|
ff003c3838181800 |
|
VISUAL
dHash
|
29f668f0e8f0b000 |
|
VISUAL
wHash
|
ff1e3c383c38f880 |
|
VISUAL
colorHash
|
080000001c0 |
|
VISUAL
cropResistant
|
00094129299100ae,d67070f0e8f0b000 |
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.