Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A5F3C76021411F3D519BC394B2B4E7AAD298F3C8DAAF8486F2DD11573AD7CA0CC5E3A5 |
|
CONTENT
ssdeep
|
3072:LOpdHvXXzF9jQO5V4MWvXuAmRaTrsNY9gslzq5K8SDwG0bEpkeWG9up:L6XXzF9jQO5V4MWvXuAmRaTrsNY9gslc |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
95a36a6aa9adaa4a |
|
VISUAL
aHash
|
e30e060706020242 |
|
VISUAL
dHash
|
4a8c0c0e0c4e6682 |
|
VISUAL
wHash
|
ffce0e0f0ee212c2 |
|
VISUAL
colorHash
|
38e08000000 |
|
VISUAL
cropResistant
|
4a8c0c0e0c4e6682 |
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 987 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.