Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T134C1D024B415486B13377FC1B8D1EE88B9D2F30EC946C27091BA43A91FC6EE559A4C72 |
|
CONTENT
ssdeep
|
48:XC9tVxc04hQnw5vWMlslNlmsd4CtWbBjmwDVJqhAjmVJVUg5mVVU15mwHj2GS4xs:S1AQKmlv5d4XbRmiYGy7LCA59J0f |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d87272d9e60f3306 |
|
VISUAL
aHash
|
c0c0001818181800 |
|
VISUAL
dHash
|
10104c32b2b2b220 |
|
VISUAL
wHash
|
e0e0383c3c3c3c3c |
|
VISUAL
colorHash
|
380000001c0 |
|
VISUAL
cropResistant
|
8398c6d54a26b152,10104c32b2b2b220 |
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 9 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.