Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11CA384607A626827205F22CFA227570E72C2C3C9DA532BE566F0D3285BF5C54BFD351A |
|
CONTENT
ssdeep
|
1536:1mY0R0zThOEAhDtG79HFF1tPRBt7c8Ct7t/TYzdt7Kw/84f8t7hd6Mt7c4Fmq4OR:EKJiTYuJenVhD777i |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
81d4bbb59ca9d582 |
|
VISUAL
aHash
|
ff0078787c606303 |
|
VISUAL
dHash
|
f6c4c0e2d4c6cbcb |
|
VISUAL
wHash
|
ff007c787c606723 |
|
VISUAL
colorHash
|
38000000180 |
|
VISUAL
cropResistant
|
c020c0d0d0d0c020,0001c06d2d840000,b6c4c0e2d4c6cbcb |
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 48 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.