AI agent security, identity, governance, cost, and the engineering behind the control plane.
Agent credentials live in more places than human credentials and last longer. Learn how agent sessions get hijacked, how tokens get replayed, and the binding techniques that stop both.
Govern AI customer-support agents: PII detection, response guardrails, escalation triggers, and tamper-evident audit logs regulators expect.
Evaluating alternatives to Noma Security for agentic AI security — red-teaming, agent containment, and where platform-bundled options fit.
Static budgets catch the disaster and miss the drift. Learn which spend signals are worth alerting on, why agents are unusually easy to baseline, and how to avoid an alert channel nobody reads.
An agent estate is a graph of agents, tools, data sources, and models. Learn what a topology map should show, which questions it answers that a list cannot, and how to keep it accurate.
AI coding agents read files, run tools, and push code autonomously. Learn the real risks — prompt injection, secret leakage — and how to contain them.
A browser-driving agent reads the open web and holds your session cookies. That combination is the highest-risk agent deployment shape in common use. Here is how to constrain it.
Enterprise AI agent governance at scale requires SSO, custom RBAC, delegated administration, and centralized policy enforcement across every team.
Standing production access for agent operators is a permanent risk in exchange for an occasional need. Learn how to build a break-glass path that is fast enough to use and controlled enough to trust.
Denial of wallet attacks do not take your service down — they run up the bill until you take it down yourself. Here is how the attack works against agentic systems and which controls actually stop it.
A pragmatic guide to AI agent security for startups: the controls that matter most when you are moving fast and have limited security resources.
AI agents are deputies acting on behalf of principals. When an attacker confuses which principal an agent is serving, its permissions become the attacker's. Here is how to structure authority so that cannot happen.
Crescendo and other multi-turn attacks distribute the payload across turns so no single message looks malicious. Learn why stateless filtering misses them and what session-level controls catch them.
How SaaS teams embedding AI agents keep multi-tenant data isolated, costs attributed per customer, and agent behavior governed at scale across tenants.
Excessive agency is what turns a model mistake into an incident. Learn the three components — excessive functionality, permissions, and autonomy — and the controls that constrain each.
Red teaming an agent is not prompt-hacking a chatbot. The objective is unauthorized action, not embarrassing text. Here is a scope, a technique set, and a scoring model that produces useful findings.
How healthcare organizations protect PHI, enforce least privilege, and prove AI agent controls to satisfy HIPAA, the EU AI Act, and auditors.
A control plane in the request path is a dependency for every agent call. Learn which components must be fail-closed, which can degrade, and how to design failure modes deliberately rather than discovering them.
A retrieval pipeline is a code path that pulls attacker-influenced content into a model's context. Learn how vector stores get poisoned, how retrieval leaks across tenants, and which controls hold.
Article 50 transparency obligations take effect 2 Aug 2026 — AI disclosure, synthetic-content marking, and what engineering teams must ship now.
The controls regulated financial firms need for AI agents: tamper-evident audit trails, scoped identity, approval gates, and on-demand regulatory evidence.
Reconstructing what an agent did, why it did it, and what it touched requires evidence most deployments never record. Learn the minimum record set and the investigation sequence that uses it.
When agents from different organizations interact, a claimed identity is worthless without verification. Learn how decentralized identifiers and verifiable credentials establish agent identity across trust boundaries.
Colorado SB 189 delayed the Colorado AI Act to January 1, 2027 and narrowed it to developer disclosure, consumer notice, and human-review duties.
