Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T115623B79732422B18B4343DAF97223FAE253827EDE630698D3648215B3D6CFCC9259C5 |
|
CONTENT
ssdeep
|
192:QofoB6CJ54t9KffOU9uEKpFmku9cuGRmKbMpBXp7sfgg8gk:QSoCWOQLKbZsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
fcaa4f2e77329408 |
|
VISUAL
aHash
|
00f9dfc7d3ff0000 |
|
VISUAL
dHash
|
553b339cb6a63762 |
|
VISUAL
wHash
|
00d9dfc7dbd3001e |
|
VISUAL
colorHash
|
060000001c0 |
|
VISUAL
cropResistant
|
553b339cb6a63762,0000003030100800,450183a2a2a2a2a2,0000103030100800 |
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 490 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.