Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14FD1E73621443A3F2A378BA8BAE4F651653DD34DC477D4A4D5EE02AE27D2E80CB33560 |
|
CONTENT
ssdeep
|
96:WMGHX46YI+kh4iHGvVZQrI83pDUIQK83kQeH83ycYbvtw:W2d4DlbV8OsnYblw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a619996666599d33 |
|
VISUAL
aHash
|
0103070707277fff |
|
VISUAL
dHash
|
fff7f7cfcfcfffff |
|
VISUAL
wHash
|
00030707073f7fff |
|
VISUAL
colorHash
|
02007000000 |
|
VISUAL
cropResistant
|
fff7f7cfcfcfffff |
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 8 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.