Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19D538230A184EA27408745C890337B5991E6B309DB234189FFF98BFB97EECB9D936115 |
|
CONTENT
ssdeep
|
1536:xKYbOsIxSrWmd3hMS7Nlo2le9l4Kr4gIvmRmFUNcdVIE7rugVmkd9ky4dJiRExXP:LO+rNZyu/5s/b0juoW6r/t44i3nEKR7x |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3788cd329d42f56 |
|
VISUAL
aHash
|
303c303c2c3c7e3f |
|
VISUAL
dHash
|
c0e851d0c8c8dcc9 |
|
VISUAL
wHash
|
003c3c3c7c3c7e3d |
|
VISUAL
colorHash
|
1ae00000000 |
|
VISUAL
cropResistant
|
02821e5646072844,e8585a337bd8d8b0,9c614d596d6d4982,aa805ad8abab80a2,c0e851d0c8c8dcc9 |
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 34 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.