Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D083A37C00471B37721B85A66970679AB365B70CCFA7880CA2FE5353EBDFC808D955A8 |
|
CONTENT
ssdeep
|
1536:2ixZtZcoI9ia2uicGas/bJ1BQy37HxLg4vf4vM+6/Xd:JxZtZvI2bJPn7HxLg434y/N |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c6ce1d9ce1313c36 |
|
VISUAL
aHash
|
383c646676060400 |
|
VISUAL
dHash
|
71e8ccccccec0c0c |
|
VISUAL
wHash
|
fc7cf6e6f6060600 |
|
VISUAL
colorHash
|
38000000000 |
|
VISUAL
cropResistant
|
71e8ccccccec0c0c |
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 193026 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.