Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T174533172B114127A816BD7C8E8113F297AB3EB2FD24DC4141AEC81A79FC7CA4F965C94 |
|
CONTENT
ssdeep
|
1536:ceM+Ru6VRK3O2jQ2TR2/R2Lm2eP2MA2IJ2xd2WQ2AA23Z2rS2CO2sb2Hex2FF2P7:cr9Qn2wL1crQMGQTyZ98q0lxsXqm |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b367338ccc8cd989 |
|
VISUAL
aHash
|
e7e7e7f7e7efffef |
|
VISUAL
dHash
|
4d4d4d050c0c8ccc |
|
VISUAL
wHash
|
c3c3c3c3c3c343c7 |
|
VISUAL
colorHash
|
07001010201 |
|
VISUAL
cropResistant
|
4d4d4d050c0c8ccc,41f0e2e0b299f9b8,4121998ccc1c1c53 |
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 44 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)