Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10383316191B2823160FF77CDE265AB1B9693DB0BCECA3BF551C4D3494BE2C85AC47248 |
|
CONTENT
ssdeep
|
1536:HDGShf1qJStGkncuoI9EEnhhvMiTd42LXghxsnh+W0kkTgI:HaSc |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b165ce99399a3619 |
|
VISUAL
aHash
|
efc3c3c3c3cfffe7 |
|
VISUAL
dHash
|
8e0e8e9e9e96000e |
|
VISUAL
wHash
|
02c3c3c3c3c3efc3 |
|
VISUAL
colorHash
|
06400018001 |
|
VISUAL
cropResistant
|
8e0e8e9e9e96000e,0d0b1b5e543a586c |
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 5 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)