TrojAI

🔥 𝗛𝗼𝘁 𝗧𝗮𝗸𝗲 𝗧𝘂𝗲𝘀𝗱𝗮𝘆𝘀 🔥 My top 5 predictions for AI Security in 2025! AI security is evolving fast, and by the end of 2025, it’ll look vastly different than it does today. Here’s where we’re headed—and why it matters: 1️ 𝗙𝗿𝗼𝗺 𝗦𝘂𝗽𝗽𝗹𝘆 𝗖𝗵𝗮𝗶𝗻 𝘁𝗼 𝗠𝗼𝗱𝗲𝗹 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿 We’ll mature past the basics of protecting AI supply chains (e.g., scanning pre-trained models). While all threats are important, the real challenge ahead is safeguarding AI behavior—ensuring models act as intended under unexpected conditions, even when under attack. AI’s power lies in its decisions, and protecting the integrity of those decisions is what makes AI security uniquely AI security. 2️ 𝗗𝗲𝗽𝘁𝗵 𝗢𝘃𝗲𝗿 𝗦𝘂𝗿𝗳𝗮𝗰𝗲-𝗟𝗲𝘃𝗲𝗹 𝗗𝗲𝗳𝗲𝗻𝘀𝗲𝘀 Organizations will require more than simple surface-level security measures. Depth of protection will matter more than ever, i.e., ensuring defenses are robust under pressure and can withstand an adaptive attacker. The security conversation will shift from checking boxes to building resilient systems that don’t fail when under attack. 3️ 𝗔𝗻𝗼𝗺𝗮𝗹𝘆 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗪𝗼𝗻’𝘁 𝗙𝗹𝘆 The notion of relying on anomaly detection to secure AI with no regard to the actual models will no longer fly—it’s just not viable at enterprise scale. To defend AI systems, organizations will adopt pentesting for each and every model. Every model has unique vulnerabilities, and uncovering those weak points will become a baseline requirement before deployment. 4️ 𝗦𝗵𝗶𝗳𝘁-𝗟𝗲𝗳𝘁 𝘁𝗼 𝗘𝗻𝗮𝗯𝗹𝗲 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 The “shift-left” philosophy—addressing security early in the lifecycle—will dominate AI development. Organizations will bake security into AI innovation from day one, instead of leaving it as an afterthought. Think thorough pentesting, secure-by-design processes, and early threat modeling for every new AI initiative. 5️ 𝗔𝗱𝘃𝗲𝗿𝘀𝗮𝗿𝗶𝗮𝗹 𝗔𝘁𝘁𝗮𝗰𝗸𝘀 𝘄𝗶𝗹𝗹 𝗖𝗮𝘂𝘀𝗲 𝗥𝗲𝗮𝗹 𝗗𝗮𝗺𝗮𝗴𝗲 2025 will bring headline-grabbing examples of adversarial attacks targeting agentic AI—systems that act autonomously to make decisions or take actions. These incidents will result in significant financial and reputational damage, underscoring that AI security differs from traditional cybersecurity and requires specialized controls for model behaviour. AI is the future, but without securing model behaviour, it’s also a big risk. What do you predict? Follow us over at TrojAI for more hot takes. #Cybersecurity #GenAI #CISO #CIO #AI #HotTakeTuesdays

🔥 𝗛𝗼𝘁 𝗧𝗮𝗸𝗲 𝗧𝘂𝗲𝘀𝗱𝗮𝘆𝘀 🔥 Canada’s $2B AI Bet: Let’s Not Waste It!  Canada has thrown down a $2 billion gauntlet in AI funding—a massive opportunity to cement our position as a global AI powerhouse. But here’s the kicker: if we play this like we’re just funding “cool research” again, we’ll stay stuck in the loop of being the talent exporter for Silicon Valley. We need to think bigger. Here’s how to make this count: 1️⃣ 𝗕𝗲𝘁 𝗼𝗻 𝗕𝗼𝗹𝗱 𝗙𝗼𝘂𝗻𝗱𝗲𝗿𝘀 Canada’s top-tier AI graduate programs produce world-class talent, but talent alone doesn’t scale—we need bold founders taking moonshots. Prioritize funding for repeat entrepreneurs with the experience to tackle big, messy problems. First-time founders matter too, but seasoned ones ignite ecosystems faster and aim higher. 2️⃣ 𝗣𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗲 𝗔𝗜 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 Generative AI is moving fast—and so are its risks. From cybersecurity threats to algorithmic misuse, we need startups and research labs laser-focused on making AI safe, secure, and trustworthy. Canada can lead here by funding ventures that tackle AI security. A secure AI ecosystem isn’t just a defensive play—it’s the foundation for long-term growth. 3️⃣ 𝗞𝗲𝗲𝗽 𝗢𝘂𝗿 𝗧𝗮𝗹𝗲𝗻𝘁 𝗮𝗻𝗱 𝗧𝗲𝗰𝗵 𝗟𝗼𝗰𝗮𝗹 Too many Canadian startups reach $100M valuations only to be acquired by American giants, taking their innovations abroad. Let’s use this $2B to create “audacious capital” that empowers founders to scale at home. With bold funding, we can grow the next OpenAI right here in Canada. The key? Don’t sell out too soon—build for the long game. 4️⃣ 𝗦𝘂𝗽𝗲𝗿𝗰𝗵𝗮𝗿𝗴𝗲 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗘𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺𝘀 Institutes like Vector Institute and Mila - Quebec Artificial Intelligence Institute are vital to Canada’s AI future, training and anchoring top talent here. Supporting them means expanding industry partnerships, boosting entrepreneurial training for researchers, and funding PhDs and postdocs. This ensures their talent feeds directly into Canadian startups and research hubs, driving a self-sustaining innovation loop. The message is clear: Canada has the talent, the funding, and the vision. Now, let’s have the guts to scale it without losing it to the highest bidder. Your move, Canada. 🍁 cc. François-Philippe Champagne, Chrystia Freeland Follow us over at TrojAI for more hot takes. #AISecurity #HotTakeTuesdays #Cybersecurity #AI #GenAI #Innovation

🔥 𝗛𝗼𝘁 𝗧𝗮𝗸𝗲 𝗧𝘂𝗲𝘀𝗱𝗮𝘆𝘀 🔥 AI security is becoming even more non-negotiable with Agentic AI. Agentic AI is having a moment, leveraging the groundwork laid by LLMs, we're now moving past copilots to agents that not only assist but autonomously plan, collaborate and execute complex actions. Compromises to such systems go beyond isolated mistakes to cascading failures at scale. Many AI security professionals have been preparing for Agentic AI since the beginning, some focusing on traditional controls like model file scanning, while others focusing on what makes AI security uniquely different, protecting the integrity of model behaviour. One thing that has been missing as we move towards Agentic AI is a definition of a canonical framework. This past week Hemant Mohapatra of Lightspeed and Meenal Nalwaya of Meta offered such a framework in their article 𝗘𝗻𝗱𝗹𝗲𝘀𝘀 𝗔𝗴𝗲𝗻𝘁𝘀, 𝗜𝗻𝗳𝗶𝗻𝗶𝘁𝗲 𝗛𝗼𝗺𝗲𝗿𝘀 (https://lnkd.in/gP5yhSk9). In it, they outline several key infrastructure components needed for Agentic AI, from agent orchestration to context management and security. Defining these components is super important as it highlights potential security gaps both with traditional and AI specific controls. Many of the large enterprise vendors are well positioned to address traditional controls but what caught my eye was the use of the term "black swan". We use this term internally at TrojAI as it describes the inherent limitation of all AI systems, i.e., the unpredictable edge cases. Edge cases in AI are long tailed and can make up to 50% of all occurrences that will present to a model, highlighting why focusing on protecting the integrity of AI behaviour is so critical and must go beyond anomaly detection which breaks down at scale. Agentic AI is here and highlights the need to continue evolving both traditional and AI specific controls. On the behavioural side, rigorous pentesting and monitoring tools continue to be non-negotiable in creating systems that can reliably and securely handle unexpected, unpredictable, black swan events. Agentic AI presents a huge opportunity and it’s exciting to see the broader industry leaning into these challenges. Follow us over at TrojAI for more hot takes. #Cybersecurity #GenAI #CISO #CIO #AI #HotTakeTuesdays