Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16A2207F8722414E5EE0397CBB92232BAA043917FDE6255D8D3648718B299CFDCC10DC6 |
|
CONTENT
ssdeep
|
192:QoroBYJ5J9FIku9cuGRmKbMpBXp7sfgg8gk:Qkog9smMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
fe2ad58e1d82d588 |
|
VISUAL
aHash
|
8381818181c3ffff |
|
VISUAL
dHash
|
2f13332b33378c0e |
|
VISUAL
wHash
|
c381818181c3ffff |
|
VISUAL
colorHash
|
16038000200 |
|
VISUAL
cropResistant
|
2f13332b33378c0e,073333332f2b2b33 |
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 490 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.