Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11303A435660151AB43BB98C1F2657F1F76D2F30F85168506ABBDD18A2FC7CB6BB20062 |
|
CONTENT
ssdeep
|
192:62VRYw8DwHb0OFGFTFnEFpFjFVF+FLMdg4JYzUm0iyrH5aQZo8UK2EQvpBnsYDGp:HlOwHb0OFGFTFEFpFjFVF+FLMT |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b33333333399998c |
|
VISUAL
aHash
|
c3c3ffffffffffff |
|
VISUAL
dHash
|
4d0d060c0c0c0404 |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
4d0d060c0c0c0404,07b7172333139390 |
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 25 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)