Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T146541ABCB1601277E037C7E5E5327E1070A732EFEB4A8244C2F956785EE6CA678594B0 |
|
CONTENT
ssdeep
|
1536:uO/LtB2TYpMyMaMyMUMyMUMo8UHDbi704gsVdxuEEW8PhQHUnHzKm8X1mKt7biYy:u+CTd7z7x7x981JcCK38v7z7x7xkhK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c03b853bc43b1de3 |
|
VISUAL
aHash
|
0040004040007f7e |
|
VISUAL
dHash
|
63a0a080a00ac1d4 |
|
VISUAL
wHash
|
d1f070c07000ffff |
|
VISUAL
colorHash
|
38208008040 |
|
VISUAL
cropResistant
|
270719204524234a,a6a7a63278707838,63a0a080a00ac1d4 |
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 1215 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.