Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19AC1B8265119602F913B46CDBF726A5AA1FFC16CD2130E04F7FC96A97BC5C49EC1288D |
|
CONTENT
ssdeep
|
96:TF1EyqzMqUSPrUKhyQfdDbz1oYMinl/lallZ4M9r00nHm52rR3duy:nERzxwOCql/lallJ00nGI1tuy |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d35444175a6a5b1f |
|
VISUAL
aHash
|
000000dc3fffffff |
|
VISUAL
dHash
|
d4aa18b979798040 |
|
VISUAL
wHash
|
0000000c9fffffff |
|
VISUAL
colorHash
|
03000038000 |
|
VISUAL
cropResistant
|
41008280a0828080,acaa39b979680240,27d4c0d4c02b9090,6f2bcf4733991531,23f3e7e5a62c2931 |
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 29 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)