Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12623A825A985D82B51DF89DD947366B460F9930AC503848EFEB8C3F613EEC6CDA73111 |
|
CONTENT
ssdeep
|
768:chL7GKxauMFwrGKxauMFwJeb7LRhnPAiEyLRhnPAiEyLRhnPAiEwf37h2vsIx/jO:SGKxauMFwrGKxauMFwcLRhnPAiEyLRhj |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b44aa54a2dfa9395 |
|
VISUAL
aHash
|
01e06fc60404ee07 |
|
VISUAL
dHash
|
0f848c2e0cadae2e |
|
VISUAL
wHash
|
81f0efc6046cee0f |
|
VISUAL
colorHash
|
30000e00008 |
|
VISUAL
cropResistant
|
80feb2baaeb88e86,0f848c2e0cadae2e |
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 103 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)