Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T129610E615051293F12678DE6B5E0B70AE1C3D64ECF9318C066FD438E8BD7D83CAD5226 |
|
CONTENT
ssdeep
|
48:nHGtR4VRH4qfH+mUNpUZAz9wSfjRMSOf+RhCgig7O6GJ29bF9p:nPZ46MNpUZZS1MS3CS7O6GJ29bF9p |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cde5621c3ee4a349 |
|
VISUAL
aHash
|
ffffff3a18181800 |
|
VISUAL
dHash
|
a2e2f2b232f2b294 |
|
VISUAL
wHash
|
fffffa3a18181800 |
|
VISUAL
colorHash
|
06c02000000 |
|
VISUAL
cropResistant
|
cadafada9a18bada,80c0c0c0c0c062c3,a2e2f2b232f2b294 |
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 400 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.