Glenn Foster

Artificial Intelligence — The Problem, The Solution, or Both? Last week, I had the privilege of speaking as a panelist at the 3rd ACFE National Fraud Conference 2025. The discussion was dynamic, thought‑provoking, and centered on one of the most pressing questions facing our industry today: Is Artificial Intelligence (AI) the problem, the solution, or both? AI as the Solution On the upside, AI offers capabilities that were unimaginable a decade ago. Machine learning models can process vast amounts of data in real time, spotting anomalies and predicting fraud patterns faster than any human team. For organizations battling increasingly sophisticated fraud schemes, this is a game‑changer. Instead of relying on outdated, rule‑based systems that react after damage is done, AI enables proactive defense. It learns, adapts, and evolves. It can flag suspicious activity before risks materialize, giving businesses the chance to act decisively. In a world where trust is currency, AI helps organizations protect both their bottom line and their reputation. AI as the Problem But here’s the catch: the same technology that empowers defenders also arms attackers. Generative AI has made it easier than ever to create convincing phishing emails, deepfakes, and synthetic identities. Automated attacks can exploit vulnerabilities at a speed and scale we’ve never seen before. In other words, AI doesn’t just level the playing field—it raises the stakes. Fraudsters are no longer limited by human capacity; they can weaponize AI to launch attacks that are faster, smarter, and harder to detect. This duality means we’re not just fighting fraud—we’re fighting AI‑powered fraud. Finding the Balance So where does that leave us? For CISOs, Fraud Risk leaders, and anyone responsible for safeguarding digital ecosystems, the challenge is clear: leverage AI responsibly while mitigating its unintended consequences. That requires three things: Robust governance frameworks: Clear policies and ethical guidelines for AI deployment are non‑negotiable. Transparency and accountability must be built into every system. Continuous monitoring: AI is powerful, but it’s not perfect. Biases, blind spots, and vulnerabilities can creep in. Regular audits and monitoring are essential to keep systems trustworthy. Collaboration across industries: Cyber threats don’t respect borders or sectors. Sharing intelligence and best practices across industries strengthens collective defenses. A united front is far more effective than isolated efforts.   Final Thought AI is neither purely the problem nor solely the solution—it’s both. The organizations that succeed will be those that recognize this duality and act decisively. Embracing AI with responsibility, foresight, and collaboration is the only way forward. The question isn’t whether AI will shape the future of fraud prevention and cybersecurity—it already is. The real question is: Will we rise to the challenge of using it wisely?

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The U.S. NIST (National Institute of Standards and Technology) has released the second public draft of the NIST Cybersecurity Framework 2.0: Cybersecurity, Enterprise Risk Management, and Workforce Management Quick-Start Guide. This follows the initial public draft of NIST SP 1308 published in March. The updated draft incorporates significant revisions based on stakeholder feedback. NIST is now reopening the document for public comment, with submissions accepted until January 7 of next year. The CSF 2.0 Quick-Start Guide is part of a series of guides released since February 26, 2024, aimed at providing tailored pathways for different audiences to adopt and operationalize the Framework more effectively. The NIST CSF 2.0 guides assist organizations in managing cybersecurity risks by helping them understand, assess, prioritize, and communicate consistently about their cybersecurity efforts, including those related to the cybersecurity workforce. The Quick-Start Guide integrates concepts from enterprise risk management, cybersecurity risk management, and workforce management, enabling organizations to enhance communication around cyber risk and make informed workforce decisions that align with actual risk conditions and planned responses. #NIST #RISKMANAGEMENT #ERM #CYBERSECURITY #OPERATIONALRESILIENCE #OPERATIONALRISK #WORKFORCE #FRAMEWORK #GUIDE

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Streamline Your Security Audits with ReguLight Security consultants often struggle with the manual overhead of mapping technical controls to diverse regulatory frameworks. ReguLight was designed to automate this process, allowing you to focus on high-level strategy rather than spreadsheet management. Key Features: • Automated Compliance Mapping: Instantly align your findings with NIST, ISO 27001, and SOC2. • Real-time Gap Analysis: Identify vulnerabilities and regulatory deviations through a unified dashboard. • Export-Ready Reporting: Generate professional, audit-grade reports with a single click. Stop wrestling with fragmented documentation. Optimize your workflow and deliver more value to your clients with ReguLight.

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Great presentation from Alan about NSA's project called Seabee designed to secure eBPF operations. Description: In recent years, security researchers and companies have looked to eBPF to build innovative security mechanisms with kernel independent bytecode and a soft guarantee of runtime safety. eBPF and the eBPF LSM in particular are especially useful in environments with bespoke security requirements where other LSMs cannot be or are not used, or kernel rebooting/recompilation is undesirable. However, eBPF programs, but their nature, present a unique security challenge: any privileged process can fully manipulate the inner workings of all eBPF objects. While SELinux provides a level of coarse-grained access control over eBPF, it is difficult for eBPF developers to tailor SELinux policy to protect their individual tools. This talk attempts to fill the gap by presenting an eBPF-based mandatory access control framework for protecting eBPF-based tools. The framework uses a configurable policy and no code change required for other tools to opt-in. We will present the design, implementation, and a policy example. We will also highlight areas for future work in the eBPF and LSM subsystems to provide more granular access controls. Github link: https://lnkd.in/exdYM8c2

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