Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11E45047AEC0C5A09707675CDE3DC4D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
3072:FfnQXhNSPGEqshNSBGEYhNS5GEzJ+MCJX2:FfnQPwMcG |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3331e4e4e1c4969 |
|
VISUAL
aHash
|
00c7c3eff9fdffff |
|
VISUAL
dHash
|
291d9f9b434be4c0 |
|
VISUAL
wHash
|
0081c1c1a1b9ffff |
|
VISUAL
colorHash
|
06000010018 |
|
VISUAL
cropResistant
|
291f9f9b434be4c0,0418597939795804,23555d214d77522e |
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 79 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)