Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10EA1AE60B462546B017BA9C2F491AF5AB5E6F30EC309D4605AFDC2FD0FE7CB1B816464 |
|
CONTENT
ssdeep
|
96:TIusWI5Q7Tg/g6+ZBTSToRtsLsY67JRYLPlrmWspT7:Hl7M/j+ZBe8bsKEG |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e938696d65c39692 |
|
VISUAL
aHash
|
8181fffffffffdf9 |
|
VISUAL
dHash
|
1713f0c0c0c06123 |
|
VISUAL
wHash
|
00007f7f7e7e7c00 |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
1713f0c0c0c06123,4040408000000000 |
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 13 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.