Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D7A27FA28D5640DBBB15B2D054172E38AD85CC3F42F24A4CA1BFD2E0F7B69D5EA1D348 |
|
CONTENT
ssdeep
|
192:29rjfQykAn9GWMW56gQjHDnyx99fIz+r3DIruLy:6fQnyAWfQToYaTu |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
92d6a0ffef290c82 |
|
VISUAL
aHash
|
7ffe7c80ff004141 |
|
VISUAL
dHash
|
8abca44e4a748f8f |
|
VISUAL
wHash
|
7ffe7ea0ef004101 |
|
VISUAL
colorHash
|
19201008040 |
|
VISUAL
cropResistant
|
6e64383870b11a6c,60f8f8e28e4c58da,80b6f17940f131f8,86da72ea9ab0b2b2,a5a6a6868d8d8989,8abca44e4a748f8f |
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 10 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.