Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DA416671101ABD375293D6D0B7A1AF1362C4C3A4CB971B5562F893AD0FC6D89CCA8922 |
|
CONTENT
ssdeep
|
48:TGupG/m+1OCSdHjhWKZqWhN4IGDkSJSJS64x/:TGu0uaOCSnWKZth/xSJSJS64x/ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
dd227788dd22dd88 |
|
VISUAL
aHash
|
0000181818180000 |
|
VISUAL
dHash
|
e0c0f0b0b2b0c870 |
|
VISUAL
wHash
|
3c3c3c3c3c3c3c3c |
|
VISUAL
colorHash
|
38006000200 |
|
VISUAL
cropResistant
|
e0c0f0b0b2b0c870 |
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 7 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)