Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A7523EB5722411A19F0353C7FD2232EAB113517EAF52669CD3A5871872D5CFEC920EC6 |
|
CONTENT
ssdeep
|
192:QoZoB6CJ54t9ANBOxCLPJ3EANku9cuGRmKbMpBXp7sfgg8gk:QeoC6H3rSsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a5ca1f1fc5e0d0ca |
|
VISUAL
aHash
|
ff07e7e707030303 |
|
VISUAL
dHash
|
7e7e8e864e765656 |
|
VISUAL
wHash
|
ff07e7e707030303 |
|
VISUAL
colorHash
|
0b000000180 |
|
VISUAL
cropResistant
|
7e7e8e864e765656,616969b9cb4b234d,b6b2b333a2e2e2ba,8069a8c2a282fa80,7fa685a4b74ea6c8 |
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.