Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16D015EB3A010540E0323D1D3A82170A47A9B360FAFCC2E1034E190D889E9EB2880A10E |
|
CONTENT
ssdeep
|
24:hR01APpXAN/yN/tlZi9ZMYkCiwvkkYvkdlra:TG6pXANaNpinMY/v1Yvv |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc663399cc663399 |
|
VISUAL
aHash
|
0000001818000000 |
|
VISUAL
dHash
|
000004b0b2080000 |
|
VISUAL
wHash
|
0f0f373f1c0c0000 |
|
VISUAL
colorHash
|
38000000000 |
|
VISUAL
cropResistant
|
000004b0b2080000 |
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 46 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)