Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FD64591AA314DD3FC58ACB9CE850AA60316C07DAFDF4C395A6798F5F4B689070D2B784 |
|
CONTENT
ssdeep
|
1536:CIIMvKjCG9KlubOkYQJeyCJForrQPmAuN/JCk/samk/samk/samk/samk/samk/e:qjC8rMuNi |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ec4e4739b3933161 |
|
VISUAL
aHash
|
0000f0ffc3c3ffff |
|
VISUAL
dHash
|
dae096209616b012 |
|
VISUAL
wHash
|
000000ffc3c3ffff |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
92b2b69393b69292,12308e9616b09602,dfdf046068848000,8c16d6242436149d |
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 11 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)