InfoQ Homepage Security Content on InfoQ
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Architecting Secure and Scalable Facial Verification Systems
When three thousand employees verify at once, synchronous API calls collapse. This article presents a four-layer architecture for high-volume face verification: client-side filtering that cut cloud costs 30%, decoupled detection and verification enabling 10x scaling, risk-based dynamic thresholds, and zero-trust privacy with consent gates and automated data purging for GDPR and HIPAA.
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/articles/chaos-engineering-ecs-payments/en/smallimage/chaos-engineering-ecs-payments-thumbnail-1788254676411.jpg)
Implementing Chaos Engineering in Financial Payment Systems: Lessons from Enterprise ECS Deployments
Standard chaos engineering assumes experiments stop cleanly, blast radius is knowable in advance, and production is fair game. Payment systems violate all three. Salim Adedeji describes ECS-specific failure modes from enterprise deployments: a 60-second DNS TTL that produced 93-second failover, retry logic amplifying database load 2.4x, and AZ rebalancing loops that generic tooling misses.
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Eliminating Long-Lived Credentials in GCP with Workload Identity Federation
Long-lived GCP service account keys are secrets that must be managed forever, are hard to rotate, and are easy to leak. Scaling Workload Identity Federation to 120+ production projects shows why it changes how machine identity is approached entirely: keys are secrets to manage, federated identities are trust relationships configured once, gated by attribute conditions.
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/articles/evolutionary-architecture-pattern/en/smallimage/evolutionary-architecture-pattern-thumbnail-1784798616611.jpg)
An Evolutionary Architecture Pattern for Managing AI’s Pace of Change
Traditional API gateways assume deterministic services and simple schemas - assumptions agentic AI breaks. Discover why enterprise engineering leaders are adopting AI Gateways as an evolutionary architecture seam. Centralize guardrails, model routing, agent identity, action policy, and semantic audit within a single control plane to prevent costly incidents while keeping core platforms stable.
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/articles/multi-agent-security-operations/en/smallimage/Multi-Agent-AI-for-Production-Security-Operations-thumb-1784628007582.jpg)
Multi-Agent AI for Production Security Operations: an A2A and MCP Architecture in a 5G Core
The bottleneck in a mature SOC is rarely analyst triage; rather, it is the detection-engineering team's ability to keep the rule base aligned with a threat landscape that evolves faster than rules can be written. Learn how multi-agent system for production security operations has reduced mean times to detect and to respond by 40% and compressed the human work required by 12x.
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/articles/aws-multi-region-signing/en/smallimage/aws-multi-region-signing-thumbnail-1783602485181.jpg)
Removing a Hidden Round Trip from a Multi-Region AWS API
When a series of regional outages forced a rethink of a multi-region AWS API, the team discovered that an obstacle to global failover was hiding in plain sight: a pre-flight discovery call baked into every client session years earlier as the only available option. This article describes what it took to remove it, and what the rollout actually cost.
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/articles/continuous-authorization-cloud/en/smallimage/continuous-authorization-cloud-thumbnail-1781599988842.jpg)
Designing Continuous Authorization for Sensitive Cloud Systems
Most cloud systems make one authorization decision at login. Everything after runs on trust established at authentication time. For systems handling regulated data, that gap is where breaches happen. This article presents a continuous authorization architecture covering risk-tiered evaluation, behavioral baselines, privacy-preserving audit trails, and a phased and incremental rollout.
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/articles/governing-ai-cloud-guide/en/smallimage/governing-ai-cloud-guide-thumbnail-1781010249930.jpg)
Governing AI in the Cloud: a Practical Guide for Architects
In this article, the author outlines a practical approach to AI governance in the cloud, covering discovery of shadow AI, data classification at creation, IAM-based enforcement, policy-as-code, and operational controls. The article shows how organizations can embed governance into delivery pipelines, balancing security, compliance, and developer productivity without relying on manual processes.
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/articles/artificial-intelligence-driven-phishing/en/smallimage/thumbnail-artificial-intelligence-driven-phishing-1780562847202.jpg)
Artificial Intelligence-Driven Phishing: How Phishing Technique Is Evolving and Implemented
In this article, the author examines how AI is transforming phishing from a manual, targeted activity into an automated and scalable attack model. The article breaks down each stage of the phishing lifecycle, showing how AI improves reconnaissance, profiling, content generation, delivery, and interaction, while outlining layered defenses that combine controls, processes, and user awareness.
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/articles/secure-ai-stack-model-production-series/en/smallimage/Article-Series-Securing-the-AI-Stack-From-Model-to-Production-thumb-image-1780040531515.jpg)
Article Series: Securing the AI Stack: from Model to Production
This series provides your roadmap for the machine age, exploring how to move from vulnerable prototypes to resilient systems through layered defense, robust MLOps, and integrated governance.
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/articles/ebpf-for-security-observability/en/smallimage/ebpf-for-security-observability-thumbnail-1778674557176.jpg)
Kernel-Level Ground Truth: Why eBPF is Replacing User-Space Agents for Security Observability
eBPF is emerging as a preferred method for security observability over traditional user-space agents. By attaching probes directly to the Linux kernel's syscall interface, it provides consistent visibility even during container-level compromises. eBPF reduces security-related CPU consumption and limits data volume by performing filtering at the kernel level, enhancing operational efficiency.
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/articles/securing-autonomous-ai-agents-kubernetes/en/smallimage/securing-autonomous-ai-agents-kubernetes-thumbnail-1777378848477.jpg)
Securing Autonomous AI Agents on Kubernetes: Trust Boundaries, Secrets, and Observability for a New Category of Cloud Workload
Autonomous AI agents break Kubernetes security assumptions with dynamic dependencies, multi-domain credentials, and unpredictable resource use. This article covers production-tested patterns: Job-based isolation, Vault for scoped short-lived credentials, a four-phase trust model from shadow mode to autonomous operation, and observability for non-deterministic reasoning cycles.