Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T171F209A1A310EFB770338778F07672959148B508DA89CE5DF2EC021AF6F9C6624F48C9 |
|
CONTENT
ssdeep
|
768:VxRalv0NIV7O/S/0SMYskiu22fw0MKmuuhyyZPsuCM8UALUAbUAMz99wgSzQESz3:2TM87L7b7MzWkjCteyeepeeYeemee9Wn |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9c6f32254be51ad2 |
|
VISUAL
aHash
|
00181c981c1ec70c |
|
VISUAL
dHash
|
b332313330b6aeb8 |
|
VISUAL
wHash
|
009b9c989c5fcf1e |
|
VISUAL
colorHash
|
19280003000 |
|
VISUAL
cropResistant
|
cba1e7a3ca5e36b0,73c99cdac6cc96c6,78c8d3a142248cc1,b332313330b6aeb8,14b0f2cfcd4c4c4c |
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 35 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.