Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F423AA603481927722B3C6C9E6257F5931EEE31FE60A49545EFF45984FD3CF8B80A862 |
|
CONTENT
ssdeep
|
768:cpMNL5ReuzpyAG9cCr1yYQKIe4a1trzLzSz1zb89sC7vtL2umy7PsAFnhO4Xh:c6bDzpyF9cCr1yhNe4a1tr/u5X89sC7D |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ee49959466636a4e |
|
VISUAL
aHash
|
fffde1e1f0f5e7e7 |
|
VISUAL
dHash
|
8c31034765a54d4d |
|
VISUAL
wHash
|
fcf9e06010c1e5e7 |
|
VISUAL
colorHash
|
06006000040 |
|
VISUAL
cropResistant
|
8c31034765a54d4d,00134f8399191919 |
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 28 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.