Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BAA3F8B1222403BE506387E8EA70EE59639FE29DF157D5509AEE83A41BC7D84FC63C50 |
|
CONTENT
ssdeep
|
1536:H7bq2xFa9eFIrSpwpNfj/nB1m9I+yOU7bKNIkl/L2oMl6zCeGAxL3qly+:4npNoJCkQ8z5L6n |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a6633389679bc626 |
|
VISUAL
aHash
|
e7e7e7e7e7e7e7e7 |
|
VISUAL
dHash
|
4c0c0c0c0c0e0c0c |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
0f0000001c0 |
|
VISUAL
cropResistant
|
0202020202020202,a0a0a0a0a0a0a0a0,36aaa21b55905755 |
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 233 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.