Ali Imran
FAST
· 2022
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I18-0847
Email
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Phone
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LinkedIn
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GitHub
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Academic
Program
BSCS
CGPA
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Year
2022
Education
SEECS
Address
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DOB
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Career
Current role
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Target role
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Skills
React JS, Go lang, Nmap, Metasploit, Masscan, Docker
Verbatim text
The exact text the LLM saw on the page (or the booklet text from the old import).
This is what powers semantic search.
Penetrato Penetrato, which is an automated penetration testing tool, is being designed with the aim of reducing the time and cost involved in the process of penetration testing. It is common practice for IT companies to do penetration tests of their networks from time to time, in order to get information about existing vulnerabilities in their system, and to protect the critical infrastructure. With each update in their softwares, companies have to repeat this whole step again so that no vulnerabilities are opened with the integration of new modules. All of these tests cost a lot of money as well as time because once the penetration test is completed, the step of report generation takes a long time as well. All of this makes this system not feasible due to huge time and cost involvement. Our tool will help solve this problem by automating the whole process of penetration testing including report generation. With this tool you can simply initiate the process at night, let the tool do its work without any supervision and view the results generated by it in the morning. This not only will solve the issue of cost but also will save you from time wastage. Another feature of penetrato is that it is very easy to use and any user even with very basic knowledge of IT can use it due to its extremely easy interface. Technology Used: React JS, Go lang, Nmap, Metasploit, Masscan, Docker Supervisor Name: Dr. Muhammad Asima Group Members: Ali Imran (I18-0847) Nauman Aziz (I18-1561) Aitzaz Ahmad (I18-0589)
AI enrichment
Ali Imran is a BSCS student who contributed to the development of Penetrato, an automated penetration testing tool designed to reduce time and cost through automation and report generation. The project utilized technologies such as React JS, Go, Nmap, Metasploit, Masscan, and Docker.
Skills (AI)
["React JS", "Go", "Nmap", "Metasploit", "Masscan", "Docker", "Penetration Testing", "Automated Reporting"]
Status: ai_done
Provenance
Source file: Graduate Directory FAST School of Computing 2022 Final Version (07-06-2022).pdfFrom job #25 page 250
Created: 1778150711