Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19002732032244D7E618BC3B4F7A07FA551ACC360DAE7D4ACE1A8C6367EC3C54CD5A2A5 |
|
CONTENT
ssdeep
|
96:TUfWUO/xK55lcFRfFY80pRFO0LVOI/c+AadFBUv7O5idLChbzQYxLPYRg/xEnVVN:uWUOcKQFOgOa/ALBz8OD |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc663399cc669999 |
|
VISUAL
aHash
|
0000181018180000 |
|
VISUAL
dHash
|
00003020b2300010 |
|
VISUAL
wHash
|
00001818ffffc3c3 |
|
VISUAL
colorHash
|
38000038000 |
|
VISUAL
cropResistant
|
00003020b2300010 |
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 30 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)