Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T164A3CD3460937C5F697FE5D4F8656F04246BDB36C2084FB9A37922B46BDE8E09822374 |
|
CONTENT
ssdeep
|
1536:Hoe9/PvyPndPz3PbwCrySLxfMJ8O0zip2hEFLuXzeTzhBeC3a:Hoe9yzF |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b39966323366cccc |
|
VISUAL
aHash
|
e7e7e7e7e7e7e7e7 |
|
VISUAL
dHash
|
4d4d4d4d4d4d4d4d |
|
VISUAL
wHash
|
0000000000000000 |
|
VISUAL
colorHash
|
0ec00010000 |
|
VISUAL
cropResistant
|
0000000000000000,0000000000000000,e310609e96862c10,735de86d7df02b57 |
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 919 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.