Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1AF92A932760141A703F799C4E560BE6FB2DAF30FC04A8555ABBD90892FD3CB67B25462 |
|
CONTENT
ssdeep
|
384:yoVES8omFhFoF8FHFtFrFKFoF5MwiPHb8:yMKTYUl3ReY5Mtfo |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3313131d9dccccc |
|
VISUAL
aHash
|
c3c3e7ffffe7efff |
|
VISUAL
dHash
|
160e0e0c1c0c0c0c |
|
VISUAL
wHash
|
03030303c7c3c3c3 |
|
VISUAL
colorHash
|
07000000c80 |
|
VISUAL
cropResistant
|
160e0e0c1c0c0c0c,10192c2818323631,5b9b93cf496d8dc9 |
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)