Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T102B35CF03658F1A665A347A3A06F2407B37D243F284D4D609354ECED62ACCDAA4A7FC5 |
|
CONTENT
ssdeep
|
1536:ER3kSs6Wytmt6UkCjrpQ4CgD9d2hr7zOUlNtbPTMnPC6T2uAtbzL8J:+NkDShvOsN50Tstbq |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9e2666d871d93931 |
|
VISUAL
aHash
|
3c3c3c3c3c3c3c3c |
|
VISUAL
dHash
|
6968687070716969 |
|
VISUAL
wHash
|
3c3c3c3c3c3c3c3c |
|
VISUAL
colorHash
|
32003200080 |
|
VISUAL
cropResistant
|
47a74de8e4e87655,6968687070716969,3333317137446d67 |
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 76 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.
Pages with identical visual appearance (based on perceptual hash)