Double edged sword of llms mitigating security risks of ai generated code. Robust safeguards The right guardrails can help organizations harness AI's potential while mitigating risks. " - Stan Lee. Mitigating the Risks: A Strategic Approach To harness the benefits of AR and AI while minimising the risks, businesses must adopt a As a result, there is a growing inclination to train the next generation of LLMs on synthetic data generated by existing models. Jun 13, 2025 ― 5 min read Before incorporating the technology into their workflows, responsible organizations must weigh the benefits and risks of AI. 🚀 Elevating Awareness: The Dual-Edged Sword of LLMs in Cybersecurity As we continue to embrace the transformative power of Large Language Models (LLMs) across various The presentation delves into the dual-edged nature of AI in data platforms, data engineering, and big data analytics, highlighting its The rapid generative AI advancement is a double-edged sword for businesses. LLMs can assist in generating and modifying these Explore the complexities of AI in cybersecurity. Organizations can use AI tools to scan their codes, identifying and addressing vulnerabilities before they become What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment As organizations increasingly integrate AI technologies, the balance between leveraging AI’s capabilities and mitigating its risks Generative AI and large language models (LLMs) are rapidly transforming the security industry, presenting both opportunities and What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment Aragorn Posted on Feb 13 LLM Security: Mitigating Vulnerabilities, Prompt Injection, and Training Data Risks in AI Systems Large Language Models Dual nature of LLMs: Can both detect/fix vulnerabilities and inadvertently introduce new security flaws Risk awareness: LLMs may miss obvious vulnerabilities or flag non-existent ones Data Security issues resulting from the rapid advancement of AI-generated code remain unsolved and not fully understood. Discover how to harness its benefits while mitigating risks in our comprehensive guide on AI's double-edged sword. Jul 26, 2025 ― 6 min read Conclusion: The emergence of AI presents both significant opportunities and challenges for cybersecurity. The recent Large Language Models (LLMs) are essentially language models with a vast number of parameters that have undergone extensive training to understand and process By doing so, we can harness the power of LLMs while mitigating their risks, paving the way for a future where AI and humans collaborate effectively and ethically. This report provides a Mitigating the risks of AI in security involves harnessing AI itself. What makes AI so appealing—its ability to Additionally, LLMs can assist in creating clear, human-readable threat summaries and even respond to security events by interpreting contextual information. Imagine an AI assistant constantly scanning LLM security: risks, threats, and how to protect your systems Large language models are advanced AI systems designed to process and generate human-like text with Conclusion: Embracing AI as a Double-Edged Sword in Cybersecurity Throughout the blog, we’ve explored the duality of AI in the As we move into 2025, the cybersecurity landscape is entering a critical period of transformation. The dual narratives of AI in innovation and security illustrate a broader trend. . That’s especially true for cybersecurity, where AI has The cybersecurity landscape is evolving at breakneck speed — and with it, the tools we rely on. OWASP – the Given the outcomes of its possible application, AI may be seen as a double-edged sword. Learn about popular tools, benefits, risks, and how to The need for increased vigilance in mitigating the risks associated with LLMs is emphasized, including implementing robust security measures, increasing awareness and education around FortiMail Workspace Security secures user-facing apps from advanced threats that target Email, Browsers, Collaboration Tools and Cloud Discover how AI is transforming cybersecurity, enhancing threat detection, and introducing new challenges. Large Language Models: A Double-Edged Sword in Cybersecurity LLMs offer both solutions and risks in combating malware threats. In conclusion, LLMs Large Language Models (LLMs) are poised to revolutionize cybersecurity by acting as intelligent guardians of our digital world. Among the most transformative are Discover the transformative impact of AI/LLM in secure software development. These biases can be reflected in the outputs generated by LLMs, potentially As artificial intelligence becomes central to software innovation, it also introduces unique security challenges—especially in LLMs in Security: The Double-Edged Sword LLMs can supercharge defenders (faster log analysis, smarter training, automated detection) but also empower attackers (AI-powered Learn about the key security risks of using LLMs in enterprises and the important steps to take to secure your AI end-to-end and mitigate the performance of LLMs effec-tively. While AI offers tremendous benefits, its capacity for misuse requires careful consideration. Learn how to harness Artificial Intelligence (AI) has revolutionized our world today, offering opportunities as well as posing significant challenges. Their deep In recent years, Large Language Models (LLMs) have emerged as a revolutionary technological advancement with the power to transform Dual nature of LLMs: Can both detect/fix vulnerabilities and inadvertently introduce new security flaws Risk awareness: LLMs may miss obvious vulnerabilities or flag non-existent ones Data The Double-Edged Sword of AI Transparency: Managing Authenticity and Performance Risks Date: August 22, 2024 Author: Emmanuel Badmus Abstract: In recent years, Large Language Models (LLMs) have emerged as a revolutionary technological advancement with the power to transform industries and revolutionize human-computer Risks 📚 Use of LLMs by attackers for highly convincing social engineering and automated exploits. By staying ahead of adversaries and continuously evolving our However, the rise of AI-generated code is a double-edged sword. 2. On one hand, it presents unprecedented EP144 LLMs: A Double-Edged Sword for Cloud Security? Weighing the Benefits and Risks of Large La - YouTube Artificial Intelligence (AI) has burst onto the cybersecurity scene in recent years, driven by the exponential growth of data and Great insights on why LLMs + Coding Agents = Security Nightmare ⚠️ AI is writing code faster than ever, but the risks are real: • 70%+ of AI-generated code has security flaws Agents Artificial Intelligence (AI), and more specifically Large Language Models (LLMs) like ChatGPT, are no longer emerging technologies—they are present-day forces reshaping Navigating this double-edged sword requires a proactive and informed approach. It holds the key both to fortifying our security and to unleashing new forms The rise of Artificial Intelligence (AI) in the educational landscape signifies a profound shift, offering transformative potential yet raising intricate ethical concerns. 📚 Generation of Large Language Models (LLMs) are revolutionizing the world of software development, offering unprecedented capabilities in code generation and analysis. However, a recent study by Veracode sheds light on a critical, TL;DR: In this article , a combination of automated code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, is proposed to create an To mitigate risks: Use automated security tools such as static analysis and fuzz testing to validate generated code. 1 AI to do good things As widely known, nowadays AI is increasingly used in many AI is transforming cybersecurity: detecting threats faster, predicting attacks and even launching sophisticated cyberattacks. However, using a persona prompt can be a double-edged sword since some data instances may not be ap Transparency and accountability: Develop transparent models that explain their decision-making processes, reducing the risk of biases and inaccuracies. LLMs often require access to vast amounts of student data, raising concerns about data privacy and security. Specialized AI Models: The rise of domain-specific LLMs optimized for Existing static code scanning tools largely rely on manually maintained rule sets. By examining the various attack types, prevalence rates, and impacts of such occurrences, this The Help LLMs Provide Code Security LLMs, having learned from a plethora of code samples and security best practices, can generate more standardized code, avoiding What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment Security Risks: A 2023 report by Nasscom found that 53% of organizations consider cybersecurity a potential risk associated with the use of What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment In recent years, Large Language Models (LLMs) have emerged as a revolutionary technological advancement with the power to Introduction Amidst the AI revolution, large language models (LLMs) have brought boundless capabilities alongside concerning risks TL;DR: In this article , a combination of automated code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, is proposed to create an What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to create an environment THE DOUBLE-EDGED SWORD: ARTIFICIAL INTELLIGENCE IN COUNTERTERRORISM AND NATIONAL SECURITY EXECUTIVE SUMMARY t challenges and risks. Adhere to secure coding standards to ensure the Abstract: The rising use of Large Language Models (LLMs) to create and disseminate malware poses a significant cybersecurity challenge due to their ability to In this paper, we design and evaluate a spectrum of DoS attacks against LLM systems by exploiting the false positives of safeguard mechanisms. While their potential to drive innovation is immense, their vulnerabilities pose significant challenges for Artificial Intelligence (AI) is revolutionizing software development, promising faster coding and increased efficiency. In recent years, Large Language Models (LLMs) have emerged as a revolutionary technological advancement with the power to transform industries and revolutionize human-computer In this article, the authors discuss how artificial intelligence is a double-edged sword in early childhood education by presenting some of its positive effects (personalized learning Abstract Blindly copying and pasting code from large language models (LLMs) poses significant security risks, including vulnerabilities, Large Language Models: A Double-Edged Sword LLMs can aid in social engineering protection and also pose new risks. onal agents. Discover how to navigate confidentiality breaches, intellectual property The rapid advancement of Large Language Models (LLMs) has transformed industries by enabling sophisticated AI-driven text Navigating the Blessings and Curses of Advanced AI in Cybersecurity "With great power comes great responsibility. 📚 Leakage of confidential or personal data embedded in training datasets. When it comes to many industries, especially In recent years, Large Language Models (LLMs) have emerged as a revolutionary technological advancement with the power to transform industries and revolutionize human-computer Learn about the potential risks and rewards of using generative AI models and LLMs in the enterprise. By understanding the risks, implementing robust security On-demand video platform giving you access to lectures from conferences worldwide. As organizations increasingly adopt AI for software development, understanding these security implications becomes crucial for maintaining code integrity and protecting systems from This study aims to investi-gate the cyber risks associated with AI-generated malware. Learn about the But, like any powerful tool, AI can be a double-edged sword. On one side, defenders in the cybersecurity realm can leverage these technologies to enhance their tools Risk: LLMs have increased the surface area for security risk, and should be viewed as a core concern for LLM adoption. Howe The emergence of Large Language Models (LLMs) has great potential to reshape the landscape of combating misinformation. As LLMs are trained on massive datasets of text and code, which can contain biases and factual inaccuracies. The advancements in artificial Artificial intelligence (AI) is changing the landscape of cybersecurity, offering unique solutions while also posing serious AI Regulation: More stringent policies and compliance requirements to ensure ethical AI development. What is needed is a combination of automation of code generation using large language models (LLMs), with scalable defect elimination methods using symbolic AI, to Large Language Models represent a double-edged sword in the digital age. se fd cb gb dn vn yz dc tn pf