Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T109C13EA2F0454F5F03135AC8B592AFA965E2E30EC44AD6D182F942E63FC7DA19C6CC61 |
|
CONTENT
ssdeep
|
96:mup87EGgJHmaZ70+8DSbnv5z75nvYPJvST8xrNH+ydSTVWd0:L87EGmn0+MG5NRQVZPMwC |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8d22ffa0d7d0c0f2 |
|
VISUAL
aHash
|
ff01011f1f1b9b9c |
|
VISUAL
dHash
|
9303b3f2f2b33272 |
|
VISUAL
wHash
|
ff01011b1f1b9b9c |
|
VISUAL
colorHash
|
1a600000080 |
|
VISUAL
cropResistant
|
0000000202000303,ce4def3f4f2b3b23,9b03b3f2f2b23272 |
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 27 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)