Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19332F7F8722415E2DE0397CAB932237AA043927EDDA35598D369875477D9CFDC800DC6 |
|
CONTENT
ssdeep
|
192:QokoBZJ5I9p5OgVMu9cuGRmKbMpBXp7sfgg8gk:QtoWL4smMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bd0a670b5c369536 |
|
VISUAL
aHash
|
00f9cf8fdfffe7e6 |
|
VISUAL
dHash
|
516b3c3c34984d0e |
|
VISUAL
wHash
|
00b98f878fcfc3c2 |
|
VISUAL
colorHash
|
07000000380 |
|
VISUAL
cropResistant
|
516b3c3c34984d0e,0000003030100800,00042032b2300c10 |
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 487 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.