Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BCA2E77010226A3F213BAB94A591FF5C60EBC30DDA576F58B39D40632BCBCD886D7285 |
|
CONTENT
ssdeep
|
384:6j0yuuAX+05K9JBIIIIeeeduprbVnjhr9tizmwrOii//G5kL+7t0a1IOA+6LFOxO:6oyuuhIIIIeeeQpjhrxIq2ADY3MXjTBV |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9bb64cec2239a276 |
|
VISUAL
aHash
|
ffffffe7e7181818 |
|
VISUAL
dHash
|
7bf1494cccf132f1 |
|
VISUAL
wHash
|
fffe6fc724181800 |
|
VISUAL
colorHash
|
06e00000000 |
|
VISUAL
cropResistant
|
7bf0484c4cf132f1,3717353a3c171b1b,b1f13338b030f1c1 |
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 639 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.