Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E983C66023215D7F218383E4E7907BAE61DAB79CCA4BD90493FC122A2BD7CC4DD27664 |
|
CONTENT
ssdeep
|
1536:+DqEX1Xon+rLkVH1QW2R3cQiQVx9s0b1LIo382oTxxEGJrW:+on+rAVH1QW2R3cQiQVx9s0JL/8Rx2kW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a97f326f02466947 |
|
VISUAL
aHash
|
008ffffffbf1ff4f |
|
VISUAL
dHash
|
1b1833030313c8bb |
|
VISUAL
wHash
|
008191f1f3f1ff07 |
|
VISUAL
colorHash
|
07000000007 |
|
VISUAL
cropResistant
|
1e1b03080303c8bb,0001030307030300 |
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 54 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)