Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D2C263BCD1A8EC32A5A2D1E172A5A76F3180CA4ACD47171042FDD369AEC3DFBED04165 |
|
CONTENT
ssdeep
|
384:/613cR7NoAXa++SpUPngVgELye2P7HfjOH/9WnNWbF2XyqMvmyP+hPqmKuB:/61M1E++STLy1j/5gml |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b4437d4e790671c6 |
|
VISUAL
aHash
|
00ffffffffffffc3 |
|
VISUAL
dHash
|
200c080c0e302d96 |
|
VISUAL
wHash
|
00ffe7e7ff0c1400 |
|
VISUAL
colorHash
|
07000018600 |
|
VISUAL
cropResistant
|
0000012b2b030000,0c0c0c0c0a302596,0010346161241000 |
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 4 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.