SAILLENTBook a DemoOriginal AI security research, flagship reports, and actionable playbooks from the SAILLENT Labs team.
The definitive analysis of runtime security trends, threat landscapes, and architectural patterns for AI agents in 2026.
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A comprehensive review of the Model Context Protocol ecosystem, identifying critical vulnerabilities and best practices.
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A high-level checklist for security leaders to evaluate organizational readiness for autonomous AI agents.
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Technical configuration and policy recommendations to secure MCP servers against tool poisoning.
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Actionable strategies and runtime controls to detect, block, and mitigate prompt injection attacks.
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A step-by-step guide to applying Zero Trust principles to AI agent identity and tool access.
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A framework for calculating risk scores and defining permissible actions for autonomous agents.
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Deep dive into designing identity-aware, least-privilege architectures for multi-agent systems.
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Technical analysis of how retrieval-augmented generation systems can be compromised at runtime.
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How to define, version, and enforce security policies for AI actions using YAML and GitOps.
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Technical disclosure of a critical vulnerability in early MCP implementations allowing unauthorized tool execution.
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Field notes from SAILLENT Labs on novel attack vectors using image inputs to bypass safety filters.
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