Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A633123463092D3EF91357E4F368B77C21AAA28AC9069004D57903762BCBEE57D3769C |
|
CONTENT
ssdeep
|
384:R76lTAM54IeglvrdiNkd23QfrnAZcsXkMOALW1S0m59HOzDPI2ymbBmINs+PI2yf:V6lTAM5Vpi0nIP15hfILm6AAVtQS3x8 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc91336c3433cfcc |
|
VISUAL
aHash
|
1e3c3c1c38380000 |
|
VISUAL
dHash
|
d6f0707860606844 |
|
VISUAL
wHash
|
7e7e3c3c383c3c20 |
|
VISUAL
colorHash
|
38000408600 |
|
VISUAL
cropResistant
|
d6f0707860606844 |
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 8 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)