Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D053FD78E50859BB1173D6C1C2323F1A7296F34FD706C1909BB847A85FD2EBBB912960 |
|
CONTENT
ssdeep
|
1536:M+bUAQ0XGB2bb7HyuMBpQO08bI1MdVB57:M+Jb7Hy7OCt |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e666669999999994 |
|
VISUAL
aHash
|
e3e3e3ffffffe7f7 |
|
VISUAL
dHash
|
4c4d45100c0c0c04 |
|
VISUAL
wHash
|
c3c3c3c3c3c3c6c3 |
|
VISUAL
colorHash
|
07200030000 |
|
VISUAL
cropResistant
|
4c4d45100c0c0c04,0a0c04002aaa2b2b |
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 31 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.