Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T187522AB9B22425E58E0383DAB92223BEF04781BEEE53469CD358825573D5CFDC824DC1 |
|
CONTENT
ssdeep
|
192:QokoBZJ5I9rNpVZULZFSMu9cuGRmKbMpBXp7sfgg8gk:QtoWXMLZFlsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b7224c0e3729553f |
|
VISUAL
aHash
|
00ffe7e7a7e7ff80 |
|
VISUAL
dHash
|
61494d4d6d6d330a |
|
VISUAL
wHash
|
00fde7a787e78380 |
|
VISUAL
colorHash
|
07001000e00 |
|
VISUAL
cropResistant
|
61494d4d6d6d330a,0000000808000000,7fdf7f5f7f733d1b,0c0c0c0d70b03030 |
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 487 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.