Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F7D34CB4B245652B067383E730ABFC12F21DA217CE1B8CB4B398E4966359C9D84777D8 |
|
CONTENT
ssdeep
|
1536:34X2FMoMNUsXocsXocsXocsXo1lUuRNka2wblHbJLwLIz9GguGOjjRnY:ErX2wd9W/guGO+ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8c7ba1942be01fab |
|
VISUAL
aHash
|
ff180000383eff10 |
|
VISUAL
dHash
|
336971a361a0a6f3 |
|
VISUAL
wHash
|
ff3c0010387eff18 |
|
VISUAL
colorHash
|
39200008003 |
|
VISUAL
cropResistant
|
fcb61abcbefe7c36,148bd8dc3e97c8fc,6ce0f8e8e1b8b8b0,64f4d262a2cefc3b,336971a261a0a6f3 |
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 254 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)