Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10D6247F05A8420DB27D2BEA4B4B17E5BA071D4F7E70F999CE1A819485EC5EB1C8C07E4 |
|
CONTENT
ssdeep
|
192:FThUw5i7dqonGFUX32xjCjYw5i7dqonGFUX324qXlF:FTh/i7dqwmMi7dqwm3VF |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
aa6a7a147e81fe42 |
|
VISUAL
aHash
|
01012103131f0f9f |
|
VISUAL
dHash
|
95c3c3d367ff7e3c |
|
VISUAL
wHash
|
0101731b1f1f1f9f |
|
VISUAL
colorHash
|
1a400038000 |
|
VISUAL
cropResistant
|
631f3e7dbb67daa5,9cdcd95b43d39393,402010910a1ae512,95c3c3d377ff7e3c |
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 1068 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.