Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16DD32B70424040DF0BCB798451923E0A59A3EDFBE10E1DBCA178E9AD0FD6FA195F16DA |
|
CONTENT
ssdeep
|
1536:wMLwMef/6/uv/rqbU/bUpqbU/bUqhbqbU/bU4MqbU/bULqEWC:eSmvDiLhbJM0SC |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bc926dc3c73a3892 |
|
VISUAL
aHash
|
ffdf8bffff818181 |
|
VISUAL
dHash
|
63333733203b3b33 |
|
VISUAL
wHash
|
b18383ffff818181 |
|
VISUAL
colorHash
|
06007000000 |
|
VISUAL
cropResistant
|
63333733203b3b33,4d16636169696b6f,27073b7b7b3b332e,724c96334d6b3323,560f2d33736d2ba7 |
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 4715 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.