Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T173F342EC8C1B157D005BFAE4D62252167E9DEA408B62EE77C3E38F258B56D18DDB3018 |
|
CONTENT
ssdeep
|
1536:KINKrJVlAnDz1rGHT2mSPWHmsUUwEf53OjBeh0JX5UL4NhnyHBrg9fNhnyHBr9NF:vqHBrg9fqHBr9qHBrNcx |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
92136c6dfc056d96 |
|
VISUAL
aHash
|
000c2c2c0c003cfc |
|
VISUAL
dHash
|
dc69c9c9c9e2dc2d |
|
VISUAL
wHash
|
060c7e6e0e007eff |
|
VISUAL
colorHash
|
39212010000 |
|
VISUAL
cropResistant
|
ccd4d8d0b2baaeb2,a001494931390990,dc69c9c9c9e2dc2d |
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 7 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)