Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1842398356211115B877BD4CAE072BF0EB293F30FD20A89C92AFD56A89FC7CB5B425560 |
|
CONTENT
ssdeep
|
384:lWbrFvFNF4FVFlFMOhnt2mrlRscKLa8naG:lWbRdXIvfMIt2slOL+G |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
99cc666699999966 |
|
VISUAL
aHash
|
1830381818180018 |
|
VISUAL
dHash
|
2020723230b22030 |
|
VISUAL
wHash
|
3c383c3c3c3c3c3c |
|
VISUAL
colorHash
|
3800b000080 |
|
VISUAL
cropResistant
|
c0e1b3f3e2e2e1a1,00280c4d4c463208,2020723230b22030 |
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 239 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)