Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D49161A2206D5F739A4361D9FA92C75A31A58305CBD7731011FCDBE85792C7CCA088A7 |
|
CONTENT
ssdeep
|
96:TGOBXPac2pDcye+QvxlL43j3A6vNgwtLpSoXghLpFPSLpnEc:/BicbVidN5ppqpVqpnH |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cccc666666279999 |
|
VISUAL
aHash
|
1818181800000000 |
|
VISUAL
dHash
|
3032b23008000000 |
|
VISUAL
wHash
|
fcfcfcfc00000000 |
|
VISUAL
colorHash
|
38000038000 |
|
VISUAL
cropResistant
|
3032b23008000000 |
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 33 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.