Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T108720AB9622002A9CF0343D6F52213BFA20792AEEA5366DCE365832573D5DBD8470DC2 |
|
CONTENT
ssdeep
|
192:QonoB6CJ54t9b1NY1aMKMt5moIGoy/qN5lRSDGgNyn1ePRYku9cuGRmKbMpBXp7B:QkoChMLmn5KqNkzNsMPRjsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
fb2ad53ed580d1c0 |
|
VISUAL
aHash
|
ff818181818181ff |
|
VISUAL
dHash
|
332733332b332bd0 |
|
VISUAL
wHash
|
ff8181818181dbff |
|
VISUAL
colorHash
|
1b0100000c0 |
|
VISUAL
cropResistant
|
332733332b332bd0,0000003232300800,2a1333232b2b3b2b,0000103030301000 |
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 485 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.