Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B49278B2A00104A303B7B9C4E670BE2EB1D6F30F891B85656EBC84942FD7DF9B561671 |
|
CONTENT
ssdeep
|
384:v3YuVrKdT0sW4FlsX4Fqsn4FZsz4F+sW4Fjs04Fdsb4FOGsB4FEsa4FDGsX4FVXQ:v5VEDmLzAdOA5Dy4Mk |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e6666623cc999999 |
|
VISUAL
aHash
|
c3c3ffffffffe7ff |
|
VISUAL
dHash
|
0f0d160c0c0c0c0c |
|
VISUAL
wHash
|
03030303e3c3c7c3 |
|
VISUAL
colorHash
|
07200038000 |
|
VISUAL
cropResistant
|
0f0d160c0c0c0c0c,8ac0a890121b99aa |
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 26 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.