Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A553C42053683A7D65274BE5F7A4F37842ADD289F69BC168E1BC1232078AC85F9339C4 |
|
CONTENT
ssdeep
|
1536:g5WUxbG+WNI/7eF/8hJJV9999a9999ig9999Ym:fh8hJz0 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c743bc389cc6ccc3 |
|
VISUAL
aHash
|
ff0020000000ffff |
|
VISUAL
dHash
|
79c3c8ccc8840220 |
|
VISUAL
wHash
|
ff0070740400ffff |
|
VISUAL
colorHash
|
020000001c0 |
|
VISUAL
cropResistant
|
0000716949710001,36cb495bdb158d0d,6d2f464c484d4d5d,1a4d8d499dd9591b,c42b3bc420003434,0010043031310c10,90c2c0ccccc8a2a0 |
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 79 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.