AI Agent Memory Poisoning: Attacks and Defenses (ASI06)
Memory poisoning implants malicious content in an AI agent's persistent state. How ASI06 attacks persist across sessions and the defenses that work.
AI agent security, identity, governance, cost, and the engineering behind the control plane.
Memory poisoning implants malicious content in an AI agent's persistent state. How ASI06 attacks persist across sessions and the defenses that work.
An MCP server registry is a supply-chain control point. What a registry entry should carry, how ratings get gamed, and why internal catalogues beat public ones.
The AI agent supply chain — models, MCP servers, tools, prompts, frameworks — and the vetting, pinning, and attestation controls against ASI04.
Retired agents keep credentials, connections, and scheduled triggers. The agent offboarding and deprovisioning sequence that actually closes them.
Agent-to-agent channels are an attack surface: spoofed peers, injected payloads, unbounded delegation. Securing A2A against OWASP ASI07.
Static allow-lists gate identity; dynamic trust scores gate scope. Learn how each works, where each falls short, and why mature programs combine both.
How one agent's error propagates through orchestrated systems — amplification, feedback loops, resource storms — and the ASI08 containment controls.
Rogue agents run with valid credentials outside governance. The kill-switch architecture — containment tiers, revocation, drills — for OWASP ASI10.
Developers add MCP servers to agents in minutes, without review. How to detect shadow MCP servers already running and make the governed path the easier one.
Guardrails, evals and monitoring each close a different AI safety gap at a different lifecycle stage. Which one to use when, and why you need all three.
Machine identity, workload identity, and agent identity are not synonyms. What each term means, where they overlap, and what agents add.
Non-human identity credentials from issuance to revocation: provisioning, scoping, rotation, monitoring, and decommissioning without sprawl.
A marketplace where publishers approve their own listings has no review at all. The listing lifecycle, why self-certification must be impossible, what to check.
The MCP 2026 authorization flow: discover metadata, choose CIMD or registered clients, use PKCE, validate the issuer, and request resource-bound tokens.
Third-party MCP servers are supply-chain risk: registry provenance, tool-description audits, version pinning, and an approval workflow that scales.
Sending every request to your best model is the costliest way to run an agent. Model routing strategies that hold quality, ones that cost more, and governance.
MCP connects agents to tools; A2A connects agents to each other. Understand how both protocols divide labor and what security controls each one demands.
A detection-focused how-to for prompt injection: pattern rules, ML classifiers, LLM judges, and behavioral signals — and where to place each one.
MCP gateway options compared as of October 2026: open-source gateways, API-gateway extensions and governance control planes, and what to look for.
Evaluating alternatives to Zenity for AI agent security: what Zenity focuses on, why teams shop the category, and a factual survey of options.
Evaluating alternatives to Lakera for LLM guardrails: what Lakera focuses on, when teams need more than a content API, and the options.
Evaluating alternatives to Prompt Security after the SentinelOne acquisition: what it covers, why buyers re-shop the category, and the options.
A ready-to-use RFP checklist for evaluating AI governance platforms: identity, policy enforcement, guardrails, spend controls, audit, and compliance.
Evaluating alternatives to Astrix Security for non-human identity governance — and when agent-native identity needs a different layer.