Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18492D563E21163755A8683DCFF2EB2EEA22344D9C9517FCD9255820EF48C8EF8606CC5 |
|
CONTENT
ssdeep
|
384:Q7oCRPCjV9ON3NxIpU9Wf/smMpBZ7eg/B:4orjalDIpU9Wcm4/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f72a552a55aa558a |
|
VISUAL
aHash
|
00c3e7e7ffe7e7e6 |
|
VISUAL
dHash
|
0b0f0f0c080c0d0e |
|
VISUAL
wHash
|
000083e7e7e7e7e6 |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
0b0f0f0c080c0d0e |
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.