Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F1E37271D358682CB17785C4E2617B9F31148286E32A0B58C7A92776F4CF977BA227CC |
|
CONTENT
ssdeep
|
3072:/dWT5LYT0xkVk1585H8BE8dOD6qqsu4Q7p:J0Yqui |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
981af261f8a6cb99 |
|
VISUAL
aHash
|
ff0018001800ffff |
|
VISUAL
dHash
|
4df0f0f0f0706000 |
|
VISUAL
wHash
|
ff003c181800ffff |
|
VISUAL
colorHash
|
1a000c00000 |
|
VISUAL
cropResistant
|
0049496986094800,6848b5b4ccb4b5b5,2c2cac6d39aeacac,680063230626632b,f4f0f0f0f0f0f0e0 |
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 3 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.