Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T119C3B6F6A32C59EC5007CBADEF2B7396132FE0FAB67D00A4956D86796183CE2E407154 |
|
CONTENT
ssdeep
|
1536:Y04EgIf4Rm3S7yOpgpdrbEFTcP6iN4qZbB17eHhsYiUBreZl5zFP7YRU6CC/8+1:YMM8QGSLqZFFtWBSoRU6PZ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
be6ac319c6c6e4c4 |
|
VISUAL
aHash
|
ff8181818181cfff |
|
VISUAL
dHash
|
393b2727373b3b18 |
|
VISUAL
wHash
|
ff85818181818fff |
|
VISUAL
colorHash
|
06006010000 |
|
VISUAL
cropResistant
|
393b2727373b3b18,8160b09abcfd7e7c,514d3323868e4d4c,0f277333331b4de5,4e5dc2c39b7b6b29,6d6521c1989b5733 |
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 162 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.