Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D0720966722422B44A4343EEFF37A2EAE21354AD9751178CD3B8421DB1C9CEDC936EC5 |
|
CONTENT
ssdeep
|
384:QIoCqrKDmzvuL6oZAIpnIvsmMpBZ7eg/B:NoHrKDmrua6m4/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f5aa55aa55aad4a0 |
|
VISUAL
aHash
|
e781e7e5e7f7e7e6 |
|
VISUAL
dHash
|
4d490d4d0d290d0a |
|
VISUAL
wHash
|
e781c300e7e781ee |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
4d490d4d0d290d0a |
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 482 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.