Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13D21EE518802CE0E65A12C92F695FDA9D8E7A74A87706900ADF540BE52FDDDDC08EEA0 |
|
CONTENT
ssdeep
|
12:hFTAyLpAe2/XlWpVdct91NOJ+lWpVa9wcJ+lWpVa9rQJ+lWpVhL1uWpVHJx3wlPm:hCOpB8XH5NOwkcwnQwCNJwl1KLN+Ayy |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e99298699a6b6b92 |
|
VISUAL
aHash
|
fdffe7e7dfc1c3ff |
|
VISUAL
dHash
|
7b544d48b4828a9c |
|
VISUAL
wHash
|
b927277fc3c34301 |
|
VISUAL
colorHash
|
07200030000 |
|
VISUAL
cropResistant
|
7b544d48b4828a9c |
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 5 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)