Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T184623B75661422E59E0243C6B93223BEE113605DFBB247DDA35C8398B2C59EDC832DCA |
|
CONTENT
ssdeep
|
192:QoJoBS5l0KtVDs/9a6GbwS75EOku9cuGRmKbMpBXp7sfgg8gk:QYoc5VA/sbesmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ff88d5a0d588d5a2 |
|
VISUAL
aHash
|
ff818181818181ff |
|
VISUAL
dHash
|
556171554d45555d |
|
VISUAL
wHash
|
ff819999818181ff |
|
VISUAL
colorHash
|
31203000000 |
|
VISUAL
cropResistant
|
556171554d45555d,956971b50d85958d |
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 484 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)