Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T140729370A4A2583F912B5AC1F4B07BAE60EAF30EDD5B4A14D3FC13AA1FD7C90E806155 |
|
CONTENT
ssdeep
|
384:3CeZxC2GkcS+oWTSnSoSS9o2JGeJ8xNaQT5QdSdSSkYTrRhWzi1m2NW:yeZxCP1xrWn3SSLAK8MiKdyS761UQU |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b0347ed0bb0f454b |
|
VISUAL
aHash
|
86c700076f6e18a5 |
|
VISUAL
dHash
|
8c8c5eae9cdc734d |
|
VISUAL
wHash
|
04c700476f7ebda5 |
|
VISUAL
colorHash
|
38001000180 |
|
VISUAL
cropResistant
|
fcfcfcfce8f87030,f0f0f0e0e0f8e0ea,8c8c5eae9cdc734d |
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 262 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)