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With Daily Installs, Third-party Apps Can Be A Important Cause For The Popularity And Attractiveness Of Facebook Or Any Online Social Media. Sadly, Cyber Criminals Get Came To The Realization That The Capability Of Using Apps For Spreading Spam And Malware. We Realize That At The Least 13% Of Facebook Apps In The Dataset Are Usually Malevolent. However With Their Findings , Several Issues Like Faux Profiles, Malicious Application Have Conjointly Full-grown. There Aren't Any Possible Method Exist To Regulate These Issues. During This Project, We Tend To Came Up With A Framework With That Automatic Detection Of Malicious Applications Is Feasible And Is Efficient. Suppose There's Facebook Application, Will The Facebook User Verify That The App Is Malicious Or Not. First We Identify A Set Of Features That Help Us To Analyze Malicious From Benign Ones. Second, Leveraging These Distinguishing Features ,where We Show That Post Of Application As Malicious With 95.9% Accuracy. Finally, We Explore The Ecosystems Of Malicious Facebook Apps And Identify Mechanisms That These Apps Use To Spread.

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