Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B9B2AB30E09010EB11B7DCD2FB707F5AA6D7F30E8939D0114B6D8A9D5FE6EE1A612486 |
|
CONTENT
ssdeep
|
192:aGSPdhwaVvaL9e5TeYoB5IpOK8VlT3hlWVl4nn2sJCrabVCCxUJuzUyc0NhM0vJC:vZ3qIqNms0OdqdYQ1KJY3hKMBQXKY |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9bdb266c26609c79 |
|
VISUAL
aHash
|
083c9c9c18180006 |
|
VISUAL
dHash
|
585838383133cbec |
|
VISUAL
wHash
|
8cbe9e9f9f380007 |
|
VISUAL
colorHash
|
380000001c0 |
|
VISUAL
cropResistant
|
e0d0b1469ee8c462,828292b2b2820082,280080e060c00002,585838383133cbec |
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 27 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.