Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19F737803E0F3566A096F7990D620F70151A7F30F95A62BD9987812B44FC3F9DB83B998 |
|
CONTENT
ssdeep
|
768:amYmfmr/f4dQuRkgFvApvApvAxvA/5qrCqO4symIhyl+obSUPw8C:tOSSq/3R4pmI1 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bc3990d096d67939 |
|
VISUAL
aHash
|
ff8181ffff81ffff |
|
VISUAL
dHash
|
b03b3b603f332d3d |
|
VISUAL
wHash
|
838181bf87819f9f |
|
VISUAL
colorHash
|
060000001c0 |
|
VISUAL
cropResistant
|
b03b3b603f332d3d,ff7f3fff9f3f3fff,00100c32b2320c10 |
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 5 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)