Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15462D8261294273FE413C78DF3F8B33991DED558D57A880BE6DD00936BC2D6ACA72285 |
|
CONTENT
ssdeep
|
192:tREauZupkS5BlnpIMxYxNB/hED9OiLU+niC3TpOev45WzOev45WeTu4OxuDJhmw:bEaIux1npIOY5hSniq1Jsa4Ggnmw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c17ec7c37c834e18 |
|
VISUAL
aHash
|
e0c00000407f7f00 |
|
VISUAL
dHash
|
ca9291d088cbdab4 |
|
VISUAL
wHash
|
f8cbc040407f7f56 |
|
VISUAL
colorHash
|
30600018000 |
|
VISUAL
cropResistant
|
b2aaaa92a2aa9a96,9737373737272735,ca9291d088cbdab4 |
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 865 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.