Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1AC02957044A9F83B6683E1DAF4B4AB1F35D1CAAADE97170107F413AC0BC7DA1CE1A519 |
|
CONTENT
ssdeep
|
192:+K2Aiqxd1JvdRgfUV+yDSw9YDAyOBk7JQ5qfcm:We1JvH0jy6DhBJBEm |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc663399cc66cc99 |
|
VISUAL
aHash
|
0000181818180000 |
|
VISUAL
dHash
|
0008303032320c10 |
|
VISUAL
wHash
|
0000383838380000 |
|
VISUAL
colorHash
|
38000e00000 |
|
VISUAL
cropResistant
|
0008303032320c10 |
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 6 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.
Pages with identical visual appearance (based on perceptual hash)