Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T133B39521900DA82F09B706D5B239972DB1A98347C3634948F7F693A9CF8ED2ED53B714 |
|
CONTENT
ssdeep
|
1536:Dk7TLiJsLAp09mFXXn0ua50ogZOeN7LsIxNrFYFP/VSXlPsAkw:w7Tuc0TLV |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c1933437eacdc076 |
|
VISUAL
aHash
|
040c7c7c7c3c02c0 |
|
VISUAL
dHash
|
9cf8e0f0c0f0b6a6 |
|
VISUAL
wHash
|
0c1c7e7c7c7e52c0 |
|
VISUAL
colorHash
|
01007000040 |
|
VISUAL
cropResistant
|
5d599b949999998d,899d9553cb93d3d3,9cf8e0f0c0f0b6a6 |
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 57 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.