Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1462457345282173E316F8BE036B1A75D63BFE308E857855D22AF72B127CECE28715685 |
|
CONTENT
ssdeep
|
1536:nSqEfOiOXFnzJRPFY4VL9qUXgDP3dkUaGiO:ofO29 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9a699a832cab9e69 |
|
VISUAL
aHash
|
01180000243c3c1c |
|
VISUAL
dHash
|
33b2330c49797979 |
|
VISUAL
wHash
|
8118183c3c7e7e7e |
|
VISUAL
colorHash
|
30409048000 |
|
VISUAL
cropResistant
|
70359a3b323d9b13,6b9f3223323649eb,1f1f7996336b7373,1f6d8f33336b2226,33b2330c49797979 |
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 251 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)