Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1420209F39220836E81D3C1BDFF66F2A4928A915FE567C4C0D3EE87A446DBC90F812610 |
|
CONTENT
ssdeep
|
96:sLJw/QhMo4bYqUzC7c0iafZTOn1oQ2wg2+3wehaBQ8VjKx3NuZkTmB0qMcSPWSiT:sLJw/yYLUY8n1ogjywAcQSyUZxBcFL/W |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
88086736d99ddc8f |
|
VISUAL
aHash
|
000019191f1f1f3f |
|
VISUAL
dHash
|
fff3b3b3b3b2f2fc |
|
VISUAL
wHash
|
00011b1b1f1f3f7f |
|
VISUAL
colorHash
|
00000240030 |
|
VISUAL
cropResistant
|
dff373737362f4f8,fff3b3b3b3b2f2fc |
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 11 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.