AI Security
AI security is not model security. The exposure sits in what surrounds the model: the prompt that reaches it, the tools it can invoke, the data that leaves with the response, and the packages underneath all three. These posts examine those failure modes as they appear in production. Related: prompt injection, DLP for AI, and egress control in the Trust Fabric.
Agentforce Governance: How to Secure Salesforce AI Agents
LLM data masking is disabled for Agentforce agents, so what an agent can reach decides what it can expose. How to govern Agentforce in seven steps.
CrewAI Security and Governance: How to Run Crews in Production
CrewAI's guardrails and hooks check an agent's work inside the run. How to put the controls that must survive a code change outside it, in seven steps.
OpenAI, Hugging Face, and the Deployment Flag
The attacking models ran with cyber refusals reduced for an eval. The responders ran with guardrails at full strength and got refused. The variable that decided who got capability was a deployment flag. OpenAI's fix concedes the missing layer and raises the harder question of who should own it.
The WOPR Brief: your monitoring stack is now an attack surface
Two Postures on the Agent Call Path
Two postures. Detect above the path. A control watches behavior and flags what looks wrong. Enforce on the path. A control sits inline, in the request itself. One tells you what happened. The other decides whether it happens.
Mythos, Daybreak, and the System Around the Model
A restricted frontier model leaked into a proxy this week before its evaluation finished. It raises the question two cyber systems already posed: is the capability the model, or the system around it? On offense, mostly the system. On defense, that answer is where the moat sits.
The Strategy Behind Open-Sourcing Shield
Free developer tools as a wedge into enterprise security is a known pattern. Here is why APERION ran it on purpose, and what we expect it to do.
The 51-Point Gap: Why Enterprise AI Security Doesn't Match Adoption
Fifty-five percent of enterprises run agentic AI. Four percent are confident in their security posture. The 51-point gap is the runtime governance market, and the reasons it exists explain why workflow and identity governance alone do not close it.
Why We Open-Sourced Shield
Agents in Cursor and Claude Code run tool calls you never see in a PR. DROP DATABASE in a generated migration. rm -rf in a cleanup script. Shield blocks the destructive operations before they execute, and we open-sourced it under Apache 2.0.
APERION: AI Sovereignty for Regulated Industries
What the LiteLLM Supply Chain Attack Means for Enterprise AI
![What Is an AI Firewall? Enterprise Guide to AI Security [2026]](https://storage.ghost.io/c/56/dd/56dd2e81-b5ad-4845-bc3a-a53d4e7c40f8/content/images/2026/09/enterprise-ai-firewall-guide.webp)
What Is an AI Firewall? Enterprise Guide to AI Security [2026]
What an AI firewall is, how it differs from a WAF, and how to deploy one in front of enterprise LLM applications in seven steps. OWASP LLM Top 10 2026 coverage and on-premises deployment.