Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BAE229B4A230D335B1C24BE8DA642528765FE1DCD7C695B4F388AF51B0D6CE8D9260CB |
|
CONTENT
ssdeep
|
384:Y7fUWegukTsRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsS0RWgMd:Y7fUWegu5hhPhleMeDGCSPxeeWmH9W |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c6313fdc6c230be8 |
|
VISUAL
aHash
|
002660f0f0f0f4f0 |
|
VISUAL
dHash
|
5cdcdac3a1e4e441 |
|
VISUAL
wHash
|
006662f0f8f8fef0 |
|
VISUAL
colorHash
|
31601400008 |
|
VISUAL
cropResistant
|
1e1e2e8efcf0e069,80c0e6343070f0e4,5cdcdac3a1e4e441 |
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 70 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)