The Vaikora blog

Field guides on AI agent security, runtime policy enforcement, LLM threat detection, and AI compliance.

Every article goes a level deeper than an overview: implementation guides, framework-level compliance, and SOC-operational detail for the people who build, secure, and audit enterprise AI.

Threats & Attacks

OWASP LLM06 Excessive Agency: AI Agent Risk ExplainedDeep dive on OWASP LLM06 Excessive Agency. What it means for production AI, why traditional least privilege fails, and how runtime control enforces it.Indirect Prompt Injection: Detection and Defense GuideHow indirect prompt injection works in RAG and tool-using AI agents. Real attack patterns, detection methods, and runtime defenses for enterprise deployments.Tool Poisoning Attacks: Malicious MCP Servers and AI AgentsHow tool poisoning works in MCP and agentic AI. Attackers embed hidden instructions in tool definitions to redirect agent behavior. Detection and defense guide.AI Jailbreak Taxonomy: Attack Categories and DefensesA complete taxonomy of AI jailbreak techniques used against enterprise LLMs. Encoding attacks, roleplay exploits, multi-turn manipulation, and runtime defenses.Prompt Engineering Security: Common Developer MistakesThe security mistakes developers make when building AI prompts. Design prompts that resist injection, leakage, and manipulation at scale.AI Agent Adversarial Attacks in Multi-Agent SystemsHow adversarial inputs propagate across multi-agent AI systems. Attack patterns, detection signals, and runtime defenses for agent orchestration security.AI Reasoning Model Security: Risks from o1, o3, Llama 4Security analysis of reasoning models. How chain-of-thought reasoning creates new attack vectors, changes jailbreak resistance, and requires different defenses.

Developer Guides

MCP Server Security: Implementation Guide for DevelopersPractical guide to securing MCP servers and tool calls. Access control, audit logging, and runtime enforcement for enterprise AI deployments.RAG Security: Protecting Retrieval-Augmented AI SystemsSecurity risks in RAG architectures and how to address them. Covers data access control, prompt injection via retrieved content, and runtime enforcement.Secure AI Agent Architecture: Developer Patterns GuideProven architecture patterns for building AI agents with security built in. Covers policy enforcement, access scoping, audit trails, and HITL design.Microsoft Copilot Studio Security: Enterprise AppSec GuideSecurity architecture and controls for Microsoft Copilot Studio. Covers data access, prompt risk, SharePoint exposure, and enterprise governance controls.LangChain Agent Security: Runtime Controls Guide | VaikoraStep-by-step guide to securing LangChain agents with runtime policy enforcement. Block PII, prevent prompt injection, and enforce access controls.OpenAI-Compatible Gateway, Security Best PracticesConfigure an OpenAI-compatible AI gateway with enterprise security controls. Policy enforcement, routing, and compliance without rewriting your app.Zero Trust for AI Agents: Architecture and ImplementationHow to apply zero trust principles to AI systems. Identity verification, least privilege enforcement, and continuous runtime inspection for AI agents.AutoGen Security Guide: Secure Multi-Agent WorkflowsSecure Microsoft AutoGen multi-agent workflows with runtime controls. Enforce policies, block data leakage, and audit agent-to-agent communications.AI Agent Red Teaming: Testing LLM Applications for RiskHow to red team AI agents and LLM applications before production. Covers prompt injection, jailbreaks, data leakage, and tool misuse testing.AI Supply Chain Security: Models, Weights, and DependenciesAssess and mitigate risk in third-party AI models and open-source components. Covers model scanning, supply chain threats, and runtime enforcement controls.AI Budget Controls: Prevent LLM Cost Overruns and API AbuseSet spend limits, rate controls, and per-key budgets for LLM APIs. Prevent runaway costs, API key abuse, and unauthorized AI usage in enterprise deployments.CrewAI Security: Controlling Multi-Role AI Agent WorkflowsSecure CrewAI multi-role agent workflows with runtime controls. Block unauthorized tool use and enforce access policies without modifying application code.Vaikora Python SDK: AI Runtime Control Setup GuideGet started with Vaikora's Python SDK for AI runtime control. Add policy enforcement, PII redaction, and audit logging to your AI application in minutes.OpenAI Realtime API Security: Enterprise Guide 2026Security considerations for the OpenAI Realtime API in enterprise. Session control, content filtering, and real-time policy enforcement for voice AI.AI Cloud Security: Architecture for AWS, Azure, and GCPSecurity architecture patterns for AI workloads across AWS, Azure, and GCP. Network isolation, IAM for AI, and inline policy enforcement for cloud AI agents.

Frameworks & Standards

EU AI Act 2026: Enterprise AI Security Compliance GuideWhat the EU AI Act means for enterprise AI systems. High-risk AI requirements, human oversight mandates, technical documentation, and compliance controls.NIST AI RMF Implementation Guide: Step-by-StepHow to implement NIST AI RMF in your organization. All four functions, Govern, Map, Measure, and Manage, with practical controls and priorities.AI TRiSM Explained: Gartner's Framework for AI SecurityWhat AI TRiSM is, why Gartner created it, and how CISOs use it to evaluate AI security vendors and build internal governance programs.MITRE ATLAS: AI Threat Techniques Mapped to Security ControlsHow to use MITRE ATLAS to model AI threats in your enterprise. Maps adversarial ML techniques to detection controls and runtime enforcement capabilities.ISO 42001: AI Management System Standard for EnterpriseWhat ISO 42001 requires for AI management systems and how to achieve certification. Governance, risk controls, documentation, and audit readiness.CSA AI Controls Matrix: Vendor Assessment FrameworkHow to use the Cloud Security Alliance AI Controls Matrix to assess AI security vendors. Control domains, assessment process, and key questions to ask.

Compliance & Audit

HIPAA and AI: Protecting PHI in Healthcare AI SystemsDeploy AI in healthcare while maintaining HIPAA compliance. PHI in LLM prompts, audit trail requirements, minimum necessary standard, and safe harbor.AI Audit Trails: What Regulators Expect from Enterprise AIWhat regulators expect from AI audit trails in 2026. Evidence requirements for SOC 2, HIPAA, GDPR, and EU AI Act, plus tamper-evident AI log design.AI Governance for Financial Services: Compliance GuideAI governance requirements for banks, insurers, and financial institutions. SR 11-7, SEC AI guidance, model risk management, and runtime controls.AI Agent Observability: Logs, Traces, and Audit TrailsHow to build complete observability into AI agent systems. Covers structured logging, event tracing, anomaly detection, and compliance-ready audit records.AI SBOM: Building a Software Bill of Materials for AIWhat an AI SBOM includes and how to build one. Covers models, dependencies, training data provenance, and how SBOM supports AI supply chain security.

Detection & SOC

AI Agent IOCs: Detection Rules for AI Threats in SIEMHow to build detection rules for AI agent threats in your SIEM. AI-specific IOCs, behavioral anomalies, and alert logic for autonomous agent activity.Microsoft Sentinel for AI Security: Integration GuideIntegrate AI agent telemetry with Microsoft Sentinel. KQL queries, detection rules, workbooks, and alert logic for AI agent security monitoring.AI Incident Response Playbook: Compromised AI AgentsIncident response playbook for compromised AI agents. Containment, investigation, evidence collection, and recovery steps for SOC and IR teams.Detecting Shadow AI: Unauthorized LLM Usage in EnterpriseHow to find unauthorized LLM API usage in your network. Traffic analysis, DNS signals, and endpoint indicators that reveal shadow AI usage.AI Threat Hunting: Hunting AI-Based Attacks in EnterpriseHow SOC teams hunt for AI-based attacks. Data sources, hunting hypotheses, behavioral anomalies, and tools for investigating AI agent threats.AI and CASB: Extending DLP to LLM TrafficWhy traditional CASB and DLP cannot inspect LLM traffic, and how to extend data loss prevention coverage to AI agents, copilots, and LLM applications.MITRE ATLAS for SOC Teams: AI Attack Detection GuideHow SOC teams apply MITRE ATLAS to AI-specific threats. Maps adversarial ML techniques to detection rules, alert priorities, and response actions.AI Behavioral Analytics: Detecting Anomalous Agent ActivityHow behavioral analytics detects AI agent anomalies before they become security incidents. Baseline modeling, anomaly categories, and alerting patterns.AI Security Data Sources: Logs and Telemetry for SOCWhat telemetry SOC teams need to detect and investigate AI security incidents. Log types, data formats, retention, and SIEM ingestion for AI.AI Threats in MDR: How Security Teams RespondHow managed detection teams handle AI security threats. Investigation workflows, evidence collection, and reporting for AI agent security incidents.Cyber Deception for AI: Honeypots for Prompt InjectionHow honeypot techniques detect prompt injection in production AI. Use deceptive prompts and canary tokens to catch attackers targeting your AI systems.

Governance & Risk

Building an AI Security Program: CISO Roadmap 2027A practical CISO roadmap for building an enterprise AI security program. Governance structure, risk assessment, controls, and program metrics.AI Governance Maturity Model: Ad Hoc to Continuous ControlAssess and improve AI governance maturity. Five levels from ad hoc to continuous control, with practical milestones and key metrics for each stage.AI Risk Board Reporting: What CISOs Need to CommunicateHow to communicate AI risk to boards of directors. The metrics, frameworks, and language that boards understand, plus common questions to prepare for.AI Risk Quantification: Measuring and Reporting AI RiskHow to quantify AI security risk for boards and risk committees. Risk scoring, appetite frameworks, and business-impact metrics for enterprise AI.

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