Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A682BC307300156722B3DAC5E6617F2EB697F30FC51AA9506AEE59860FC7CB5BB610B0 |
|
CONTENT
ssdeep
|
192:67VRsLMfHypFtOFZFYF3FBFuF6RFNYSOMUpCUFf9Ltc3V4vjP:KIMfHypFtOFZFYF3FBFuF6gr1cFS |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ccccce6666333133 |
|
VISUAL
aHash
|
383c181810181818 |
|
VISUAL
dHash
|
a2b0303030303030 |
|
VISUAL
wHash
|
3c3c3c18183c3c3c |
|
VISUAL
colorHash
|
38000038008 |
|
VISUAL
cropResistant
|
a2b0303030303030 |
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.