Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17C82DE35660011BB13B795C0EAB17E2EB1DAF30FC40A8826A6BDD1CA2FD3CB57661571 |
|
CONTENT
ssdeep
|
384:w5rNsnxObCFieFEAFAqF7/FBBFXBFmWFFMCpG2TGjFo5A8ft5YgCeW:wtNNGiaEgA+7NBzXzmCFMCpG2TGjFo5W |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3333323cccccccc |
|
VISUAL
aHash
|
c3c3e7f7e7e7efff |
|
VISUAL
dHash
|
0e0d0c0c0c0c0c04 |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07000000c00 |
|
VISUAL
cropResistant
|
0e0d0c0c0c0c0c04 |
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 22 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.