Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T172532272B104127A816BD7C8E8113F297AB3EB2FD24DC4145AEC81A79FC7CA4F965C94 |
|
CONTENT
ssdeep
|
1536:cRM+Ru6JRK3O2cQ2/R2DR2Cm2iP2nA2dJ22d2DQ2hA23Z2VS2RO2Nb2Aex2lF2ja:cy90oCwglPElbRQv/IC+sgxxslu7 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3763398d98cdd04 |
|
VISUAL
aHash
|
e7c7e3e7e7efffef |
|
VISUAL
dHash
|
4d4d4d040c0c8ccc |
|
VISUAL
wHash
|
c3c3c3c3c3c343c7 |
|
VISUAL
colorHash
|
070c1000000 |
|
VISUAL
cropResistant
|
4d4d4d040c0c8ccc,4f13bcb6b2b17959 |
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 44 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.