Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F722F8EA02004B7E4583C1ACFAA6F534522AC1EEDA73C9D2E3EE077742D3C44E9174A0 |
|
CONTENT
ssdeep
|
192:aHK8SYN133NkBwaY1jywAcQSyUZxBcFL/W:aq8SYN133NkBwaY12NjaNcFK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d3bd40e641197373 |
|
VISUAL
aHash
|
00ffffffffffff00 |
|
VISUAL
dHash
|
904408320c0c40c0 |
|
VISUAL
wHash
|
003fefff07070000 |
|
VISUAL
colorHash
|
060000001c0 |
|
VISUAL
cropResistant
|
48240a32300c1000,0080809090808000,02d0c996d1d0d120 |
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 10 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)