Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D4E240DF55C020324122BDE3B4130A4F9B8B9D3DC901FEA9BA5942E71DCDE9961867CB |
|
CONTENT
ssdeep
|
384:sCY0O82LS/UmLGwEXeCgfw1/gSSlCr+TN9K:sC0CHLGxXD4K |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9fbe60709f40c11f |
|
VISUAL
aHash
|
00ffffffff0000ff |
|
VISUAL
dHash
|
793f706060b0a963 |
|
VISUAL
wHash
|
0087ffffbf0000b9 |
|
VISUAL
colorHash
|
060000001c0 |
|
VISUAL
cropResistant
|
793f7f7060683020,6063639160608000,0000010202020000,16484ea1a9696904 |
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 5 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.