Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10202E8F39214476E5593C1ACFFA2F2A4929A815FE56BD5C0D2EE879445CBCA0FC23720 |
|
CONTENT
ssdeep
|
96:XhNM8MNME/Z46gUzC7c0iafZTOn1oQIwg2+3wehaBQ8VjKx3NuZkTmB0qMcSPWSK:xN7K1/+pUY8n1oGjywAcQSyUZxBcFL/W |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
881d662399d9cc5f |
|
VISUAL
aHash
|
00001818181d1903 |
|
VISUAL
dHash
|
fff3b2b2b3b2f3cf |
|
VISUAL
wHash
|
00011b1f1f1f2f7f |
|
VISUAL
colorHash
|
00000440018 |
|
VISUAL
cropResistant
|
dff3b2b2b3b3f3df,fff3b2b2b3b2f3cf,001824b2b2320c10 |
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 8 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.
Pages with identical visual appearance (based on perceptual hash)