Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10EC20F32A046049B01B3D8D1FA72BF59A5C7F30BC6254964BFAC468B4FC7DBCB5582A1 |
|
CONTENT
ssdeep
|
384:f90D6hl3DkVNlY9rbPWYXM+z6T8iT+Yba8KSVc:F0gl3DkVnY9rbPWYXM+z6TJjjKOc |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc3333cc36999936 |
|
VISUAL
aHash
|
1818181818181818 |
|
VISUAL
dHash
|
3032323232b23232 |
|
VISUAL
wHash
|
3c3c383c3c3c3c3c |
|
VISUAL
colorHash
|
38007000000 |
|
VISUAL
cropResistant
|
3032323232b23232 |
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 578 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.