Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F6542A597211312A41A721D2A43F060F7236EAB9B207850CB15BD6EC7E6CC8962FFF75 |
|
CONTENT
ssdeep
|
6144:0pBPWoM8qpSpre9u7Chn1S/Y7nHQJLs33oSNF92xoNq:4BPWoM8qcprou7CXPnOLNSNFU |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
caa1b75d934c6453 |
|
VISUAL
aHash
|
ffff0018381010ff |
|
VISUAL
dHash
|
e8c0013369b0f0e8 |
|
VISUAL
wHash
|
ffff0018381810ff |
|
VISUAL
colorHash
|
02000000043 |
|
VISUAL
cropResistant
|
0080c4c0d0c4c001,56594d5d53d12426,4e48a94c69a95454,21314cd4b3ee4f45,4f263849a9a81657,8280825edec28080,6961e8c42e964468,0000000010a3a250,81b33361c9b2b2e8 |
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 36 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.