Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E7332160B251B67204B3D3D2D4253F4936BAF32ED106E760DAA842A71FC3CB5BD512E6 |
|
CONTENT
ssdeep
|
1536:uRywRyUTkioTkiJTkifTkiOaYdMFbmgwth7mht7DUHAa:2TkioTkiJTkifTkirYOL7DUHT |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c94bb6b4e548c2ba |
|
VISUAL
aHash
|
ff8998f0fbffffff |
|
VISUAL
dHash
|
5979312373381301 |
|
VISUAL
wHash
|
bd08189089ff81ff |
|
VISUAL
colorHash
|
07007008000 |
|
VISUAL
cropResistant
|
5979312373381301,2756182d934e3918 |
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 37 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)