Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D3F1C6E2626493AD5083C4BCFFA2F190524E916EE2A2C9D0E69E57B405E7DD1F613C90 |
|
CONTENT
ssdeep
|
96:TG6FXvmYr4KELkfYhkf3cBYkfj1IPwg2+3wehaBQ8VjKx3NuZkTmB0qMcSPWSicO:a6VbgLBl1bjywAcQSyUZxBcFL/W |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f722dc88dd8a7522 |
|
VISUAL
aHash
|
ffe7e7efffe7e7fe |
|
VISUAL
dHash
|
204d4d48584c4d32 |
|
VISUAL
wHash
|
272703032f27273e |
|
VISUAL
colorHash
|
07000080007 |
|
VISUAL
cropResistant
|
204d4d48584c4d32,0e69f06aeac2ea65 |
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 12 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.