LLM Threats to Businesses Research
Budget: $30 – $250 USD
I need a fully referenced research paper that explains what large-language-model (LLM) AI is and, more importantly, how malicious actors are already leveraging it to defraud companies and breach corporate data. The focus is squarely on the impact to businesses: think automated spear-phishing with ChatGPT-style prompts, deepfake customer-service bots harvesting credentials, code-generation exploits, and rapid discovery of vulnerabilities using GPT-4, Claude, or similar tools.
Please weave credible expert opinions and analyses throughout the paper—quotes from leading cybersecurity researchers, white-hat hackers, Gartner or NIST commentary, peer-reviewed journal insights, and conference proceedings are all welcome. If you come across standout case studies or hard statistics that strengthen an argument, feel free to incorporate them, but expert perspective is the non-negotiable element.
Scope and structure I’m envisioning
• Title page, abstract, and table of contents
• Clear definition of LLM technology and its evolution
• Detailed breakdown of attack vectors against businesses (social-engineering, malware creation, data-exfiltration, supply-chain compromise, etc.) mapped where possible to frameworks such as MITRE ATT&CK or OWASP
• Expert commentary on emerging trends and likely future threats
• Defensive measures, governance recommendations, and relevant legal or compliance considerations
• Conclusion summarising key takeaways
• Full reference list in APA style, with in-text citations
Acceptance criteria
• Original, non-plagiarised content, 4,000–5,000 words
• Minimum eight distinct expert sources cited
• Delivered as an editable Word document (and optional PDF)
• Completed no later than 16 July 2026, with a brief outline shared midway for alignment
If this matches your expertise in cyber-security research and technical writing, I look forward to collaborating with you.
Please weave credible expert opinions and analyses throughout the paper—quotes from leading cybersecurity researchers, white-hat hackers, Gartner or NIST commentary, peer-reviewed journal insights, and conference proceedings are all welcome. If you come across standout case studies or hard statistics that strengthen an argument, feel free to incorporate them, but expert perspective is the non-negotiable element.
Scope and structure I’m envisioning
• Title page, abstract, and table of contents
• Clear definition of LLM technology and its evolution
• Detailed breakdown of attack vectors against businesses (social-engineering, malware creation, data-exfiltration, supply-chain compromise, etc.) mapped where possible to frameworks such as MITRE ATT&CK or OWASP
• Expert commentary on emerging trends and likely future threats
• Defensive measures, governance recommendations, and relevant legal or compliance considerations
• Conclusion summarising key takeaways
• Full reference list in APA style, with in-text citations
Acceptance criteria
• Original, non-plagiarised content, 4,000–5,000 words
• Minimum eight distinct expert sources cited
• Delivered as an editable Word document (and optional PDF)
• Completed no later than 16 July 2026, with a brief outline shared midway for alignment
If this matches your expertise in cyber-security research and technical writing, I look forward to collaborating with you.