Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T130A2DB72710111EB03B7CAC1FA71BE2AA6A7F30FD10A9115AAED42952FD3CF4B551A70 |
|
CONTENT
ssdeep
|
384:ZrLAyuoUdta3lAee36HYfxZZ1RQFnAK329OKrN93KivBbKOf9GFBFfFKFLDaLp7D:FYyFjzteOpv |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
996633666c7e4c19 |
|
VISUAL
aHash
|
0008183c181c0c1c |
|
VISUAL
dHash
|
0dda323232283a32 |
|
VISUAL
wHash
|
00083c3c3c3c3c3c |
|
VISUAL
colorHash
|
38006000080 |
|
VISUAL
cropResistant
|
0dda323232283a32 |
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 359 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.