Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12A1498754360236E16138FACF7D2B3B9705D628DD95BC889E36C826527CBCC6AE111EC |
|
CONTENT
ssdeep
|
1536:hIA/HrahfRLUBgQwQj1LN+dShiC+iOaAxejZ57HJ4KXrHq+Bd9ogp2wQ5/ZTuQjn:mymPIfM |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8e708bec87fc1887 |
|
VISUAL
aHash
|
ff0000002000ff3f |
|
VISUAL
dHash
|
29183864e6246673 |
|
VISUAL
wHash
|
ffdc08003090ff3f |
|
VISUAL
colorHash
|
06c00000000 |
|
VISUAL
cropResistant
|
1208291182303080,b642483a394d56b2,4a6a6a6a6a6a4955,262626d06969e363,0008103010100800,18383824e6e63426,75c165d5c7f0d845 |
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 24 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)