Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18E51457F0305133BE595C7C4AB62A02EE2D7D506F095A0D4EBDA95D70E8EFE358B0860 |
|
CONTENT
ssdeep
|
48:uoov3JnK7kUteUtgYW1eymJqRyNPhtLHM3IU8sLFEUUq/o6jgwZY5v4b:PBtkMhtc8sH1o6jggYCb |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b333cccc233399cc |
|
VISUAL
aHash
|
ffffe7e7ffffffff |
|
VISUAL
dHash
|
0010080c10100800 |
|
VISUAL
wHash
|
f0f0e0e03c3c3c3c |
|
VISUAL
colorHash
|
00007000000 |
|
VISUAL
cropResistant
|
0010080c10100800 |
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 3091 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)