Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T140F36C703540B53F45B383E2B0987972A259D21ECB0B8D70F318E55A77D6CAB943B69C |
|
CONTENT
ssdeep
|
1536:8MJNkNLNfXzYEzEbfN2iq2qGhULXHrd+s1rdLR16L41tSE+w+XMmbV1SqpMatIWd:PNkNLNfXzYUEbTptJZUPAaSDB |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bf3e61c1c1453535 |
|
VISUAL
aHash
|
000000ffffffffff |
|
VISUAL
dHash
|
3215557560535353 |
|
VISUAL
wHash
|
00000001bfffffff |
|
VISUAL
colorHash
|
0f000400038 |
|
VISUAL
cropResistant
|
5515553168535353,71e8cc9696cce871,8146b6b2b64e8082,3474b6b696963634 |
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 412 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.