Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18142C9315100703F8B271AC572723B2EB1F7D2EDDB674450D3FC1BA92BD6CA2A962161 |
|
CONTENT
ssdeep
|
384:T8eT+IeGiVAx5Y0GMGzGtGvGuGpHkL72owObY49au1A/yIGJF:T8eSLAx5Y0R8KQVqHkLJpbY27AwJF |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ad5752a9a95ca156 |
|
VISUAL
aHash
|
0707838383839083 |
|
VISUAL
dHash
|
7d0c0d0f0f0b3427 |
|
VISUAL
wHash
|
8f8787878383d3c3 |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
7d0c0d0f0f0b3427,9064a53d37336820,014545495945459c,110d31b3b34db101 |
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 161 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.