Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DF332420B6042AAF016B95C0EC70AF5A7097E35EC20B44647EF8925D2FC3C71F95A9BD |
|
CONTENT
ssdeep
|
1536:k84WKEwK6hX1kaxedqLQ7BfIQmV4OU/89ULzULjgL9PLOVLm:k84b2Xcg48x2m |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8153d62df640a57b |
|
VISUAL
aHash
|
00004840033b7fff |
|
VISUAL
dHash
|
d0d0d29a92d6f300 |
|
VISUAL
wHash
|
003848c80b3bffff |
|
VISUAL
colorHash
|
0fc00000000 |
|
VISUAL
cropResistant
|
4646d5d68c94ad67,f2e890e292a1c1c8,92d6d6d6d3f00004,ec7cc0c286c76638,d6d0d29a9a92d6d3 |
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 24 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.