Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FD2393369504313B063716CDF02A7B5EF0E3C34ECA4354A4B3AD57CA0BDBD94E96A929 |
|
CONTENT
ssdeep
|
768:Rn0zO1dzEhtDkqHJqtLj35bd6ggumG/S8DeqYrNfGgTcqqa1IuloNE341CMKWr9j:Rn0zO1dzEhtDkqHJqtLj35bd6ggumG/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a756a92d5cb4b158 |
|
VISUAL
aHash
|
0130040610070727 |
|
VISUAL
dHash
|
47c8ccece0dfcfcf |
|
VISUAL
wHash
|
03782e3e3c0f076f |
|
VISUAL
colorHash
|
30200003001 |
|
VISUAL
cropResistant
|
6863fad9d9d9e6ea,47c8ccece0dfcfcf,016928174d30b10d |
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 1657 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.