Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T139E21DB0521019AF0AC3BC90A1D73E876573CAEAE12F9C9CA2B8549C1FD0FA5C1D57E5 |
|
CONTENT
ssdeep
|
384:s4SStOXjsEv37u3QXE3NZGXoq1L/ugvauklLcX:sAAF7E3CLRDX |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
83a7af70f028f92a |
|
VISUAL
aHash
|
672f3f070040017f |
|
VISUAL
dHash
|
cfccefac8cd2e3f7 |
|
VISUAL
wHash
|
ff3f3f070040017f |
|
VISUAL
colorHash
|
06481000000 |
|
VISUAL
cropResistant
|
cfcfccccebefaeac,aaaaaaaaaaaaaaaa,8282828280828282,22a5b6cac8e47476,e6e3b3b3afe75656,cfccefec8cd4e3f3 |
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 73 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.