Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BCC1C731911D647FA12342C8BB32BE2A51D7D16DE3230C10F9BC86ABB6DAC45DD2358D |
|
CONTENT
ssdeep
|
96:TNJIUDtz93iTweIyaXP/ljN6EEZ4Mk21r9s1FTRTU:kUDtz93xVEs2p9sDG |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
974257bde01d52c6 |
|
VISUAL
aHash
|
00000004ffffffff |
|
VISUAL
dHash
|
d455ccec005e5415 |
|
VISUAL
wHash
|
00000004ffffbfff |
|
VISUAL
colorHash
|
0e200000018 |
|
VISUAL
cropResistant
|
800080c0c2c08080,ec00cf5656555501,d0dc5555c4ccf4ec,ffdedfdfcedd978f |
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 46 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.