Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T115B34430A065952B019FB2E3F539871A23D3D30EDE534BE6E3E883694BCDE65AC13159 |
|
CONTENT
ssdeep
|
384:b7h7lHEzseRTd8N2D66Yzo4SRRcESOLYdzoKnRIk8Sdb9tBQUXnFEjJUIFYHM34V:b7nHs566IiQ3uiSYs3yGqAs6ABHeQr |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9212ed6cc36d6d92 |
|
VISUAL
aHash
|
000404240400ffff |
|
VISUAL
dHash
|
da4dccc8cd08cb43 |
|
VISUAL
wHash
|
00047e3e6c00ffff |
|
VISUAL
colorHash
|
39000038000 |
|
VISUAL
cropResistant
|
f3c1a4d2d361bc1c,b77462727674c1e3,2d2c2c8989ad2c2d,44cbe3c409000006,d48dcde8cccd3947 |
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 23 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.