Sec4AI4Sec’s Post

🔍 In-Depth Research on Cybersecure Software Development 🔍 At Golfdale Consulting, we are proud to have been commissioned by Security Compass to conduct comprehensive research on AI and cybersecurity. The interactive research report "Cybersecure Software Development: Management Views on AI" revealed crucial insights for the industry, including the need for: ⛓️ Integrating AI in Threat Modeling to significantly enhance the accuracy and efficiency of identifying potential security risks. ⛓️ Integrating AI in Automated Security Testing to reduce software development time to market while maintaining high-security standards. Building on these insights, Security Compass just unveiled their game-changing SD Elements 2024.2, which includes: 🌟 AI Assistant Navigator Beta: Transform threat modeling with instant, tailored security insights. 🌟 GitHub Integration: Automate survey responses and generate threat models seamlessly. 🌟 13,000+ Expert-Vetted Practices: Unrivaled guidance for secure AI integration. Does your company develop software? Be sure to check out Security Compass' post linked in the comments. #Cybersecurity #AI #Innovation #SecurityCompass #SDElements #ThreatModeling #SecurityByDesign #Research #2024Insights

🔒 𝗧𝗵𝗲 𝗛𝗶𝗱𝗱𝗲𝗻 𝗥𝗶𝘀𝗸𝘀 𝗼𝗳 𝗔𝗜-𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝗱 𝗖𝗼𝗱𝗲: 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂 𝗡𝗲𝗲𝗱 𝘁𝗼 𝗞𝗻𝗼𝘄 🚀 𝗔𝗜 𝗰𝗼𝗱𝗲 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝘁𝗼𝗼𝗹𝘀 like GPT-4, Code Llama, and WizardCoder are transforming software development. With productivity gains and faster workflows, they’re becoming staples in developers’ toolkits. But there’s a catch: ⚠️ 𝗡𝗲𝗮𝗿𝗹𝘆 𝟱𝟬% 𝗼𝗳 𝗔𝗜-𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝗱 𝗰𝗼𝗱𝗲 𝘀𝗻𝗶𝗽𝗽𝗲𝘁𝘀 contain bugs that could lead to significant cybersecurity vulnerabilities, as highlighted in a recent report from the Center for Security and Emerging Technology (CSET). 💼 𝗨𝗻𝗲𝘃𝗲𝗻 𝗶𝗺𝗽𝗮𝗰𝘁: Larger organizations with robust security processes can manage these risks, but smaller companies may struggle due to limited resources. 🤖 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗯𝗶𝗮𝘀: Developers often trust AI outputs too much, skipping crucial security reviews. 📌 𝗪𝗵𝘆 𝗶𝘁 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 AI-generated code is becoming a critical part of the software supply chain. Without proper safeguards, insecure outputs could create vulnerabilities, affecting organizations and the wider cybersecurity ecosystem. 🌟 𝗧𝗮𝗸𝗲 𝗔𝗰𝘁𝗶𝗼𝗻 Stakeholders - developers, organizations, and policymakers—must collaborate to ensure security remains a top priority alongside innovation. 💬 𝗬𝗼𝘂𝗿 𝗧𝘂𝗿𝗻! How can businesses leverage AI tools while staying secure? Let’s discuss below! #Cybersecurity #AIInnovation #SecureCoding #TechLeadership

AI-driven fuzzing is revolutionizing cybersecurity by addressing long-standing challenges in vulnerability detection. Traditional fuzzing methods rely on random or semi-random input generation to stress-test software systems and identify weaknesses. However, they often miss deeply hidden vulnerabilities, especially in complex, legacy systems. AI-driven fuzzing transforms this approach by bringing intelligence, adaptability, and efficiency to the process. How AI-Driven Fuzzing Works Intelligent Input Generation: Unlike random fuzzing, AI-driven fuzzing uses machine learning (ML) models to generate targeted inputs. These inputs are tailored to exploit specific weaknesses, dramatically improving the likelihood of uncovering vulnerabilities. Dynamic Learning: AI systems continuously learn from testing results, adapting inputs to focus on high-risk areas of the code. This iterative process enhances precision over time. Code Coverage Optimization: AI fuzzers prioritize areas of the software with incomplete test coverage, ensuring that even overlooked or poorly documented sections are rigorously evaluated. Advantages of AI-Driven Fuzzing Uncovering Legacy System Vulnerabilities: Decades-old software often underpins critical infrastructure but lacks robust defenses. AI fuzzing shines here, exposing vulnerabilities that traditional methods might overlook. Enhanced Speed and Scale: By leveraging automation and ML, AI fuzzers can evaluate complex systems faster and more thoroughly than manual or traditional approaches. Reduced False Positives: AI systems refine their analysis to differentiate between exploitable vulnerabilities and benign issues, minimizing noise for security teams. Customizable for Emerging Threats: AI-driven fuzzing can be tailored to mimic evolving attack patterns, ensuring systems remain resilient against the latest cybersecurity threats. Real-World Impact Retrospective Vulnerability Discovery: AI fuzzing has exposed vulnerabilities in systems believed to be secure for years, including foundational protocols like SSL/TLS or file systems used in critical infrastructure. Proactive Threat Mitigation: Developers can identify and patch vulnerabilities during development, reducing the risk of zero-day exploits after deployment. Challenges and Considerations Training Data Dependency: AI fuzzers require high-quality, diverse training data to be effective. Gaps in training data can limit their performance. Adversarial Risk: Attackers could use AI fuzzing tools for malicious purposes, requiring developers to stay one step ahead. Integration with Existing Workflows: Companies must adapt their development pipelines to incorporate AI-driven fuzzing, which may involve upfront investment and training.

🚀 Exciting Developments in R&D: Revolutionising Secure Software Technologies! 🔍 Problem Context: In today's tech landscape, the human element in developing secure software often takes a backseat. We've identified this as a critical issue as it poses significant risks to cybersecurity. Our aim? To pioneer empirical studies with an interdisciplinary approach, focusing on emerging complex software engineering paradigms. 💡 Our Solutions/Projects: Mining Software Repositories for Emerging Tech Knowledge: We're delving deep into software repositories to extract crucial insights for emerging technologies. DevSecOps via Shared Mental Models: We're fostering shared mental models within intra-organisational software development teams, promoting a culture of DevSecOps. 🔧 Our Core Capabilities Text Mining for Trend Analysis: We mine software repositories for trends and new knowledge. Qualitative & Quantitative Data Analysis: Our expertise lies in analysing vast quantities of data in text mining studies. Human-Computer Interaction (HCI) Research: We're developing innovative software interaction methods to strengthen the relationship between the human and user. Anti-Phishing Interventions: We provide support to developers and practitioners in addressing challenges from individual, technical, and organisational perspectives. Contact us to learn more or collaborate! #Cybersecurity #Innovation #DevSecOps

🚀 𝐀𝐈-𝐃𝐫𝐢𝐯𝐞𝐧 𝐅𝐮𝐳𝐳𝐢𝐧𝐠: 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐂𝐲𝐛𝐞𝐫𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐛𝐲 𝐄𝐱𝐩𝐨𝐬𝐢𝐧𝐠 𝐃𝐞𝐜𝐚𝐝𝐞𝐬-𝐎𝐥𝐝 𝐕𝐮𝐥𝐧𝐞𝐫𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬 🛡️ For nearly 20 years, a critical flaw (CVE-2024-9143) in the OpenSSL library—essential for secure global communication—remained hidden. Leveraging AI-powered tools and large language models (LLMs), Google’s OSS-Fuzz project finally uncovered this vulnerability, enabling a timely patch. This groundbreaking achievement is more than just a technical milestone; it’s a testament to the transformative potential of AI in shaping the future of cybersecurity. 🔍 Google’s OSS-Fuzz marks a paradigm shift in vulnerability detection. By expanding code coverage by over 370,000 lines across 272 C/C++ projects, it unearthed 26 previously hidden vulnerabilities, including a flaw in the cJSON library. These results underscore how traditional testing methods, while valuable, can struggle to address the complexity of modern software. Complementary advancements, such as Big Sleep’s identification of new memory-safety flaws and Vulnhuntr’s success in uncovering zero-days in Python projects, reinforce the indispensable role of AI in achieving unmatched precision and scale. Together, these innovations illustrate that the future of secure software development lies in AI-augmented solutions. 🌟 The discovery of CVE-2024-9143 is a pivotal moment that underscores why organizations must integrate AI into their cybersecurity strategies. As a cybersecurity professional, I see three key insights from this milestone: first, AI excels at processing immense complexity with speed; second, it empowers teams to focus on strategic imperatives by automating repetitive tasks; and third, it fosters collaboration—bringing together the best of human ingenuity and AI precision to redefine vulnerability management. Organizations must understand that adopting AI is no longer optional but essential to outpace evolving cyber threats. 💡 What are the biggest challenges your team faces in scaling vulnerability detection? How do you see the balance between AI tools and human expertise evolving in cybersecurity? https://lnkd.in/gYwSyXSh #securesoftware #vulnerabilitymanagement #aiincybersecurity #cybersecurity #cyberriskmanagement

AI code tools are becoming widespread in software development, despite some bans and concerns. In a survey, a significant 47% of respondents showed interest in allowing AI to make unsupervised changes to code. However, generative AI still struggles with secure coding practices, making AI-driven security tools essential. Source: InfoSecurity Magazine Is your organization leveraging AI in software development? Contact GlobalWave Consulting to explore security solutions for your organization. www.GlobalwaveCI.com #AI #CyberSecurity #SoftwareDevelopment #AITools #GlobalWaveConsulting #TechNews #Innovation #DigitalTransformation #ITSecurity #AIInTech July 30, 2024 at 08:12AM via Instagram https://lnkd.in/eJ6JEy33

A Privacy Engineering Primer. I'm presenting an all-new workshop at Australian Information Security Association (AISA) #CyberCon this week, Thursday Nov 28, in Melbourne. MyPOV: “Privacy Engineering” is not simply privacy for engineers. Rather, it is the practice of resolving privacy requirements in complex systems in concert with other often conflicting design demands. To help technologists, architects, developers and project managers better engage with privacy, I treat it as a non-functional requirement, alongside other objectives such as cybersecurity, performance, usability and other considerations, and provide three practical tools for systems designers to resolve these different needs: 1. Privacy Policy for Design Thinking 2. Personal Information Flow Mapping 3. Privacy-informed Threat & Risk Assessment. After a recap of privacy principles and Privacy Impact Assessment (PIA) methods, the three tools will be presented, and the class will participate in applying the methods to topical real-life challenges arising from Generative AI. More information at https://lnkd.in/gGfnh_Nv. #CyberCon2024 #AustralianCyberConference #PrivacyEngineering #PIA #DataProtection #Privacy #PrivacyByDesign #AI #GenAI

Over 100 AI tools to increase business productivity 🔹Today, SDAIA | سدايا published a comprehensive and interactive guide to more than 100 artificial intelligence tools that help increase business productivity, whether for individuals, employees, companies, or various entities and institutions. 🔹 These tools are classified by fields into (12) areas, namely: ▪️Marketing ▪️Design ▪️Programming ▪️Cyber Security ▪️education ▪️Research ▪️medicine ▪️Law ▪️Architecture ▪️Project Management ▪️Human Resources ▪️Accounting 🔹These tools have been selected from the best leading and emerging technology companies.

🚨 Unlock the Future of Code Security with AI! 🚨 🗓️ Join us LIVE on January 29th for an exclusive webinar to discover AquilaX, the world’s leading AI-powered vulnerability detection platform! 🔐 Why Attend? In a digital world, security is non-negotiable. One vulnerability can disrupt everything. AquilaX is the AI-powered platform that helps developers and security engineers identify and fix vulnerabilities faster, ensuring safer, more resilient infrastructure. 💡 What You'll Learn:     🔧 For Developers: Supercharge your security workflow with AI-driven insights.     🛡️ For Security Engineers: Detect and address vulnerabilities in record time.     🌍 For Everyone: See how AquilaX is securing the digital world we all rely on. 🎤 Presented by Abhey Sharma, Head of Engineering at AquilaX, showcasing how our platform is revolutionizing code security. 🎯 BONUS: Start protecting your code today with a FREE Trial of AquilaX --> https://shorturl.at/Wvnq4 🔍 Webinar Details: 📅 Day and Date: Wednesday, January 29th ⏰ Time: ·       3:30 PM (Athens, Helsinki, Bucharest) ·       2:30 PM (Berlin, Rome, Madrid) ·       1:30 PM (London, Dublin, Lisbon) ·       09:00 AM (New York, Toronto, Miami) ⏳ Duration: 1 hour + 15-minute Q&A Don't miss out! Register now to secure your spot 👉https://shorturl.at/3U1Nl (You can register easily by clicking 'Next' without signing in to Google.) For any queries, doubts, or consultations, please feel free to contact us at [email protected] or DM us directly. We're thrilled to reveal how AI is transforming the future of code security!🚀 #AI #CyberSecurity #TechInnovation #Webinar #AppSec #DevOps #DevSecOps #ApplicationSecurity #CodeSecurity #SecurityEngineering #SoftwareDevelopment #VulnerabilityManagement #ThreatDetection #SecureCoding #TechLeadership #FutureofTech #AquilaX

The rapid adoption of generative AI and LLMs is transforming industries, particularly in software development, where 81% of IT professionals are already leveraging these technologies. However, as organizations innovate, they must prioritize robust frameworks to address emerging privacy and security challenges. Balancing efficiency with ethical considerations will be crucial for sustainable growth. Organizations should proactively develop governance strategies to mitigate risks associated with AI deployment. #cybersecurity #GenerativeAI #software