Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C163D92421003B3FA567CB4EF2D8B29A430DE149D6165C1FFACA027B2ADAD69CD1F594 |
|
CONTENT
ssdeep
|
768:xha6nIORA8eR8R7kRJRe41UwH11aR41UDfO1yJwtr+JQOZyiNg7r04rhBrr11W11:4CRpuw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ec4cb3b35c4c4c59 |
|
VISUAL
aHash
|
10ebd1d1d9f7efff |
|
VISUAL
dHash
|
2813b3a3372c0a00 |
|
VISUAL
wHash
|
0081d1d1d1d3e3ff |
|
VISUAL
colorHash
|
38002000180 |
|
VISUAL
cropResistant
|
2813b3a3372c0a00 |
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 12862 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)