Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T143B21C30B886AC370197C2D59B765B1B7AE5E342CB0347059BF8C3ACABDAE5BDD11148 |
|
CONTENT
ssdeep
|
384:7FBcPBNOGcDT90AAnAsD0AiKAnOAYMiHAtSPBNekEPdBH:iBATWQLKUOIUwgBUkEPdBH |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b36699999c666433 |
|
VISUAL
aHash
|
ffe7c3c3ffffe7ef |
|
VISUAL
dHash
|
104d4e0e101c0c1c |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07400010080 |
|
VISUAL
cropResistant
|
104d4e0e101c0c1c,2525272fc7a6c4c4 |
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 14539 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.