Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1AA816673D505092B266786E4FED6F36890F2430AC56BE885A3FD81CA5BC6DB09C73324 |
|
CONTENT
ssdeep
|
96:TubM8MMM/ME/e46gUzC7c0iafZTOn1oQY:Cb7lM1/zpUY8n1o1 |
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 32 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)