Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1438309E83519F5270AB343A710DF15037278122B980E4D60B254FE9FA6FDC5AB067BE9 |
|
CONTENT
ssdeep
|
1536:ROtJYBL7lUuRNka2wblHbJLwLIz9GguGOjjRnY:CYVrX2wd9W/guGO+ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bc4c4b635c3c1e1e |
|
VISUAL
aHash
|
00fb9f9fffefefff |
|
VISUAL
dHash
|
33022436140a1838 |
|
VISUAL
wHash
|
00819783f78f8f8f |
|
VISUAL
colorHash
|
07000000180 |
|
VISUAL
cropResistant
|
33022436140a1838,002c52b2b1b35252 |
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 35 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.