Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FBC174625118503BC2374ACD7E715B1EA2BBD26DD1270E04F7ED8AE96BC1C89DD1348D |
|
CONTENT
ssdeep
|
96:TSCEyqzMqb4zUKlmYZhG3z1oYMiP9l/lalNZ4M10iUh0hrZyfP+rbw15WiW6:vERzx7Cq9l/lalNJgfWHy5Wo |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cd5c0d0d3e4b5f05 |
|
VISUAL
aHash
|
0000c89cfffbfbff |
|
VISUAL
dHash
|
72acaa39acd2d2a8 |
|
VISUAL
wHash
|
00000088fffbfbff |
|
VISUAL
colorHash
|
02000030000 |
|
VISUAL
cropResistant
|
2282a2c2c2a28022,acaa39302cd2d2a8,8d626272620d9290,6f2bcf6733991131,23f3e7e5a62c2931 |
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 44 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.