Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C3A276B3A184693F1157C2C4A732BB4EA3A3D24ED59E78A16AFC43161EC3D71E812532 |
|
CONTENT
ssdeep
|
192:Wk7kzqpPjSkZAzE3zxYUT+jaktBL4q6yVgQm78sWyZFm0AgQYWQWzPh+mkknkD:WukzqpeSYiaakLL4q6yVgQm78xYqkD |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e46c9b93b2306cce |
|
VISUAL
aHash
|
c3c3c3c3ffffffff |
|
VISUAL
dHash
|
1696969600161818 |
|
VISUAL
wHash
|
81c3c3c3cbc7c3c3 |
|
VISUAL
colorHash
|
07081000080 |
|
VISUAL
cropResistant
|
1696969600161818,686869e9e3e273c6 |
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 5 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.