Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F7F3B4729061243F563FB2ECF231B76DB197934BCE5643D9E6E841241BE7C99AC23818 |
|
CONTENT
ssdeep
|
1536:oTVkH0tUP5FPX82WDW33pAcZic8gp6NAX3pzG8wG2ksRKRLM/peHeSeexedeEeeq:oWBh9MLo3pAcZic8RuXZzlwMP/IzUcc |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cb3e166949161e6b |
|
VISUAL
aHash
|
00af879ff9f9ff7c |
|
VISUAL
dHash
|
71593f335323c3e9 |
|
VISUAL
wHash
|
008f818ba9f9fb3c |
|
VISUAL
colorHash
|
07006000200 |
|
VISUAL
cropResistant
|
715d3b335323c3e9,000010cc69696906,4501537169610145 |
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 587 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)