Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11A724D76721412B24A4303D6AA2631FF9213D17ED7921FBCD3684258729B8FDC175DCA |
|
CONTENT
ssdeep
|
384:QkcoC1lw0FPDQC/Ti0DbQNI2zMSXy6ZusmMpBZ7eg/B:TcoopBDHGqVqwqm4/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e6229989f21a6f6a |
|
VISUAL
aHash
|
ff7f006060003bff |
|
VISUAL
dHash
|
dce66dcdcd62720c |
|
VISUAL
wHash
|
ffff006060003aff |
|
VISUAL
colorHash
|
07030000000 |
|
VISUAL
cropResistant
|
dce66dcdcd62720c,cccece4a6c6cbc9c,cfffffb4bdffe7f6,60acb3f1d37d4c8c |
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 485 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)