Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18AF24371A085353B41A7C1C0E739FB4AA3C291CAE96ED18067FC879C9FC6E95DC12926 |
|
CONTENT
ssdeep
|
384:0s8kj4DsEvM2GBrATz11z9VoV2Ik9zNUl:0hkAjvqBrAn19oV2BDUl |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9919131c3ee6e2e6 |
|
VISUAL
aHash
|
0f0fff1f0fffffff |
|
VISUAL
dHash
|
7d7488703480f0d0 |
|
VISUAL
wHash
|
050f2f0f0f0f0f2f |
|
VISUAL
colorHash
|
07040000006 |
|
VISUAL
cropResistant
|
7d7488703480f0d0,c591c5c181812dad,0020067171200c10 |
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 5 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.
Pages with identical visual appearance (based on perceptual hash)