Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15722F7F8722404E5DE0397CAB93232BAA043917FEE5255D8D3688758B2A9DFDCC50DC6 |
|
CONTENT
ssdeep
|
192:QoyoBS5lwNSeNvku9cuGRmKbMpBXp7sfgg8gk:Q3ocw2smMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f520d78ad7a8d48a |
|
VISUAL
aHash
|
c3c3c3c3ffffffff |
|
VISUAL
dHash
|
969696962b060102 |
|
VISUAL
wHash
|
c0c0c0c08080f2f2 |
|
VISUAL
colorHash
|
0e032000000 |
|
VISUAL
cropResistant
|
969696962b060102,2b17321333333332 |
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 484 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.