Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B1531F306442993B42D799D59236172AA3F18348CA130649FEF9D7FA6FDFC68CE27160 |
|
CONTENT
ssdeep
|
768:/IsIx/jkgfAs6+5wkxWI73Gmkl1As6s69F9FOlfFWUf7sd4dPA2:gsIxIgIXg73GmklaXX9jFO9FJ7fS2 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ee26918b4b1b1e2e |
|
VISUAL
aHash
|
fdf781d1b1f1fdfe |
|
VISUAL
dHash
|
71a5252767659b04 |
|
VISUAL
wHash
|
bdf1808131b0f9fc |
|
VISUAL
colorHash
|
07203000080 |
|
VISUAL
cropResistant
|
71a5252767659b04,1d5c74333a302a8f,814193195ddccc2d |
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 43 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)