Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12872C66A12041B7B678B00F5E592BF8DE2A6734EC63BECC473E4D3960BD5C40AD96488 |
|
CONTENT
ssdeep
|
384:ahfU9s53OWFfJ4CJ73DZsFVXI5AaEc81lBDfA:ahfU9W3OWFh4CtyFr1lm |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c04f953fd02bc2f8 |
|
VISUAL
aHash
|
7e3e5000000019ff |
|
VISUAL
dHash
|
f2f0a080b200b3b2 |
|
VISUAL
wHash
|
7e7e78404000dbff |
|
VISUAL
colorHash
|
38000038000 |
|
VISUAL
cropResistant
|
3b33736925dc969c,f2f0a080b200b3b2 |
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 207148 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)