Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F7932AB43A59F5665AF3439310AF1103B378562B540E4C60B350ECAE76BCC9BA067FDA |
|
CONTENT
ssdeep
|
1536:Ht5XgfbsQJo2h2wV92949tVPTMn5UCAuu0kYg28G:Ht5XkXMA2i9nYAIkYf |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b434494b4739b9b6 |
|
VISUAL
aHash
|
0000d7f7f79fffff |
|
VISUAL
dHash
|
122f160f4c303400 |
|
VISUAL
wHash
|
00c3c3f7f70090ff |
|
VISUAL
colorHash
|
07001000006 |
|
VISUAL
cropResistant
|
4c4c220032320012,2e16960c2c300000,0020c0c8c8c83040 |
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 32 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.