Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1ED721B79621422F49F0383D6EE3522FAE113A07DBB5212DCE3A8C25872D9DAD8535DC5 |
|
CONTENT
ssdeep
|
192:QoToBS5lmVry4vqLMtIBAsuuYOS0l/HuZC3ku9cuGRmKbMpBXp7sfgg8gk:Qsoco9qL3Boudl2ZpsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e4939b6d4964966c |
|
VISUAL
aHash
|
fffff7f3f3f3d3f2 |
|
VISUAL
dHash
|
82d0c48686e6a6a6 |
|
VISUAL
wHash
|
7a7e764252725272 |
|
VISUAL
colorHash
|
070020001c0 |
|
VISUAL
cropResistant
|
82d0c48686e6a6a6,381ab135313a3e31 |
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 484 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.