Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19F649429E8F38A3F453EB5C0C0A52F1452CBD34767CA63F4C1A945A95B92E9DAC074BC |
|
CONTENT
ssdeep
|
6144:6zLRbKC1DcwKC1DcXYNbawa4/Ky7Fdmd5mJ:4LRbKC1DcwKC1DcXYN1KX5mJ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9c9570708778d5e5 |
|
VISUAL
aHash
|
1c3fbfbfbf848000 |
|
VISUAL
dHash
|
b4a46460643d3d13 |
|
VISUAL
wHash
|
043fbfbfbf948000 |
|
VISUAL
colorHash
|
07000010240 |
|
VISUAL
cropResistant
|
b4a46460643d3d13 |
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 16 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.