Trust Minimization in Digital Systems

One of the most interesting aspects of my last few roles, including my current work at Humain, is operating at the intersection of AI and advanced security/encryption techniques from zero-knowledge proof systems to the extension of Zero Trust principles into the agentic world. In traditional Zero Trust, we authenticate users and devices. In the agentic world, the “user” could be an autonomous agent — a system that reasons, acts, and interacts with data and other agents, often at machine speed. That changes everything. To secure this new ecosystem, Zero Trust must evolve from static identity verification to dynamic trust orchestration, where every action, decision, and data exchange is continuously verified, contextual, and cryptographically enforced. 1. Agent Identity and Attestation Every agent must have a verifiable, cryptographically signed identity and prove its integrity at runtime; not just who you are, but what you’re running: the model, weights, policy context, and data provenance. 2. Intent-Aware Policy Enforcement Access control must become intent-aware, so agents act only within bounded policy domains defined by explicit goals, permissions, and ethical constraints — continuously verified by embedded governance logic. 3. Least Privilege and Time-Bound Access Agents must operate under least privilege, with access granted only for the minimum scope and durationrequired. In fast-moving agentic environments, time-limited trust becomes an essential safeguard. 4. Assumed Breach and Blast Radius Containment We must assume some agents or environments will be compromised. Security design should minimise impact through microsegmentation, strict trust boundaries, and dynamic reassessment of communication between agents. 5. Encrypted Cognition As models process sensitive data, confidential AI becomes essential where combining homomorphic encryption, secure enclaves, and multi-party computation can ensure that the model cannot “see” the data it processes. Zero Trust now extends into the reasoning process itself. 6. Adaptive Trust Graphs Agents, services, and humans form dynamic trust graphs that evolve based on behaviour and context. Continuous telemetry and anomaly detection allow these graphs to adjust privileges in real time based on risk. 7. Cryptographic Provenance Every output, decision, summary, or recommendation must be traceable back to the data, model, and policy that produced it. Provenance becomes the new perimeter. 8. Autonomous Audit and Forensics Every action should be self-auditing, cryptographically signed, and non-repudiable forming the foundation for verifiable operations and compliance. 9. Machine-to-Machine Governance As agents begin to negotiate, transact, and collaborate, Zero Trust must extend into inter-agent diplomacy, embedding ethics, accountability, and policy directly into machine communication. If you’re working on AI security, agent governance, or confidential computation, I’d love to connect.

🙃Happy April Fools’ Day!🙃 Today reminds us to question everything, particularly in the digital realm. In the spirit of not falling for pranks, hoaxes, or convincingly fake emails, remember: 1️⃣Don’t implicitly trust a digital identity. Identities must be verified for authenticity. 2️⃣Don’t implicitly trust a device. Devices can be compromised and need to be continually monitored and assessed. 3️⃣Don't implicitly trust a network. The backbone of our digital communications, networks must be secured and treated with a discerning eye. Not all traffic is benign. 4️⃣Don't implicitly trust applications and workloads. Apps, though they serve as productivity tools, can harbor vulnerabilities or malicious code. 5️⃣Don't implicitly trust data. Our most valuable asset, data, demands protection from manipulation and theft. 🛡️Zero Trust principles teach us to use diverse signals to contextually analyze sessions and dynamically assess confidence in identities, devices, networks, applications, and data. Applying a Zero Trust mindset helps build a security posture that adapts to evolving threats, ensuring that trust is continuously earned and validated. 📖To deepen your understanding of these principles and apply them in a structured manner, explore the Zero Trust Maturity Model by the Cybersecurity and Infrastructure Security Agency (CISA). It offers a roadmap for organizations to assess their current posture and navigate their journey toward a comprehensive Zero Trust environment. Learn more about the CISA Zero Trust Maturity Model at: https://lnkd.in/eeFzBAbg On this day of jests and jokes, let’s remember: In the realm of cybersecurity, it's April Fools’ Day every day. Don’t be fooled. #computersecurity #informationsecurity #technology #innovation

The proliferation of #GenAI and now the autonomous #AIAgents are putting challenges in more ways than one. There's a very interesting take on AI usage against one of most popular concepts in security, viz. #zerotrust. Zero Trust, working on the principle of “never trust, always verify" is an effective #cyberstartegy in today's world of vanishing perimeters, with transactions moving from within the premises to applications and infra hosted on the cloud & virtual devices, back to users' (employees, vendors, providers) personal devices and so on. Zero trust implies that every access request is authenticated, authorized and validated, every single time with least privilege, which means that there's no 'access all' or 'once authenticated, authorized across multiple resources'. Zero trust ensures that an attacker or a malicious packet or rogue agent cannot have a seamless lateral movement across the network. But here's where it gets interesting with the use of Gen and #agenticAI. #AI tools need access to all relevant data, applications, devices in order for them to function effectively. A segmented / microsegmented network, requiring authentication and validation each time under a zero trust architecture can be a productivity block for an AI agent, can even make it malfunction. Possible areas of friction can include :    🔸 Agentic AI thrives on autonomy, making decisions and executing tasks without human intervention, whereas zero trust demands verification at each step    🔸 AI models evolve through continuous learning, while zero trust policies with static access rules may restrict availability  🔸 GenAI systems perform best with large, diverse datasets. Zero trust restricts access to minimize risk. But here's the silver lining; Zero Trust does not oppose AI adoption. Designed thoughtfully, it can complement AI driven transformations. Some recommended strategies include : 🔅 Identity : Treat each AI Agent, model or API call as a distinct (non-human) identity #NHI, subject to authentication and authorization. 🔅 Least Privilege : Ensure that AI workloads have granular access rules defined so that they don’t inherit implicit trust across resources and access the minimum datasets necessary 🔅 Segmentation : Use micro-segmentation to isolate / restrict AI workloads to required critical systems 🔅 Continuous Monitoring : Use AI based analytics and anomaly detection to strengthen incident response. For AI specific risks, examples of triggers can be anomalous prompt patterns, instruction override commands, system commands leading to data exfiltration, filtering outputs and so on. 🔑 Organizations need to define a strategic balance between AI led innovation and managing risks against misuse or compromise. 🔑 Advanced AI governance principles are required to align with adaptive AI models 🔑 For CIOs and CISOs, resilience will now demand improvising AI-aware Zero Trust architectures. #cybersecurity #artificialintelligence #AI #leastprivilege

This article challenges one of the most entrenched assumptions in cybersecurity, that people are responsible for breaches in systems they never controlled. Despite decades of technological evolution, security is still stored online passwords, keys, and credentials sit right next to the data they’re supposed to protect. And as one chart makes painfully clear, even 18-character passwords with symbols can now be cracked instantly. The article argues that true digital trust must be redefined: Not through static encryption. Not through user-blaming compliance. But through presence-based validation trust that’s generated only when someone is actively there and cannot be spoofed or cloned. Drawing on personal reflection, it calls out how security has become something users are told to manage but are never allowed to truly own. It challenges tech leaders and regulators to stop retrofitting broken systems and instead design architectures that don’t store secrets because security should never have been stored to begin with. #DigitalTrust #ZeroTrust #PostQuantumSecurity #BehavioralEncryption #AIresilience #DataOwnership #CyberEthics #SCADAsecurity #DeepfakeDefense #PrivacyByDesign #ConsentIsNotControl #TrustByPresence

Your Vendor's Breach is Your Problem: The Supply Chain Security Wake-Up Call. The recent NYT report on the bank data hack via a third-party vendor confirms a critical truth: https://lnkd.in/eqTaNTX2 In today's interconnected world, your security perimeter is only as strong as your weakest link. This is not just a "big bank" problem. If major financial institutions can be exposed by vendors, smaller firms who often share those same suppliers, or rely on vendors with less mature controls, are equally (if not more) vulnerable. Data confidentiality and system access are non-negotiable privileges that must be earned and constantly re-verified. To the question, "Is there nothing that can be done?"—the answer is a definitive NO. We must move past reactive audits and embrace a proactive posture. 4 Essential Steps to Protect Your Confidential Data: 1. Shift to Continuous Monitoring: Annual questionnaires are insufficient. Implement tools for real-time risk scoring and continuous assessment of vendor security posture. 2. Zero Trust for Third Parties: Apply the principle of least privilege. Vendors should only have access to the bare minimum data and systems absolutely required for their service, and no more. 3. Mandate Cyber Contractual Clauses: Ensure contracts legally enforce strong security controls, prompt breach notification, and right-to-audit clauses. 4. Data Minimization: Review every vendor relationship. If a third party doesn't truly need access to confidential data, remove it. Reduce the attack surface immediately. The fallout from a breach is astronomical. The investment in robust TPRM and cyber oversight is a strategic necessity, not a compliance burden. Leaders, the time to vet and monitor is now.