Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CBB23D70614AAA3712A3A3D2F7755B6F32D0830ACA43171A93F8C3AC4BE3D81DE17955 |
|
CONTENT
ssdeep
|
384:Z+TQe+44vrZRVX61W678RMITO/HOHFDIesbj241EGxZFPY5n1PsE89+2Eg:ZTe+44FRVXsW67IMIa/HOHFD2bj2KRxJ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
92c56db5a49393a5 |
|
VISUAL
aHash
|
02006c6c7c0c0c01 |
|
VISUAL
dHash
|
86e1c9c9c9c93897 |
|
VISUAL
wHash
|
62707c7c7e6e0e03 |
|
VISUAL
colorHash
|
38041000480 |
|
VISUAL
cropResistant
|
f07524343534529b,e884a2a1c9b4686a,d4486469e49c4300,86e1c9c9c9c93897 |
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 54 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.
Pages with identical visual appearance (based on perceptual hash)