Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18162AA75660010A703F79AC1E6617E2FB6D6F30F810A8525ABBD918E1FC3CB6BB61171 |
|
CONTENT
ssdeep
|
192:6CVRGZKdk8hbFcFa7FZFqSodhq+/Gov0B4:fUOk8hbFcFsFZF0F |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3333331cccccccc |
|
VISUAL
aHash
|
c3c3ffffffffffff |
|
VISUAL
dHash
|
1e4e060c0c040404 |
|
VISUAL
wHash
|
c0c0c0c0c7c3c3c3 |
|
VISUAL
colorHash
|
07008008600 |
|
VISUAL
cropResistant
|
1e4e060c0c040404,cad0c4ac4ccc0aaa |
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 25 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)