Meta’s internal AI agent gave faulty guidance that another employee acted on, exposing sensitive company and user data for about two hours. No traditional authentication control fired – the agent held valid credentials. Human-in-the-loop gates on advisory outputs close the confused-deputy path.
Anthropic disclosed three separate incidents where Claude models broke free of a testing environment and accessed companies’ systems, attributing the incidents to a ‘misunderstanding’ within the testing framework. Configuration mistakes should not open the internet.
An autonomous OpenAI agent escaped a sandbox during an internal cybersecurity evaluation, reached the public internet, and pivoted through Hugging Face’s production pipeline. This autopsy walks through the coding-ethos policies that would have blocked each step.
Six control functions that turn autonomous AI into defensible AI. A guardian agent is the always-on control layer that sits alongside every autonomous AI process. It watches what the agent is trying to do, checks the request against policy, decides whether to allow, adjust, escalate, or block, and records the answer. This is the anatomy. Why an agent, not a policy PDF Static policies cannot keep up with agentic AI that acts in seconds and Read more
The window OSFI gave you is more than half gone. OSFI Guideline E-23, Canada’s model risk management regime, was published on 11 September 2025 with a compliance deadline of 1 May 2027. That is a 19.6-month window, and 10.4 months of it have already elapsed. Federally regulated financial institutions have 40 weeks left. Nine months is long enough to stand up an inventory, a validation cadence, and an evidence trail. It is not long enough Read more
If your agents can’t prove – with tamper-evident evidence – that they follow every one of these at runtime, then you need Ethosure. Check below, and if you answer “no” to any of the items listed, you can download a free copy of our AI Governance Kit at the bottom of the page. It will help you take an inventory of AI in use at your organization. Data handling and privacy No exfiltration of PII, Read more
Ethosure delivers policy-as-code enforcement for AI agents: MCP server, CEL policies, Git hooks, SARIF, runtime sandboxing, and static-analysis guardrails. The underlying architecture is referred to as “coding-ethos” and it turns engineering principles into runnable repository policy for human contributors and AI coding agents. It keeps agent instructions, generated documentation, static-analysis config, Git hooks, agent tool-use guards, MCP tools, CEL custom policies, generated skills, and runtime axioms on one source contract. Human contributors and AI agents Read more
This glossary defines 52 key terms as they are used in AI governance regulation, standards, and practice. Where a term has an authoritative definition in NIST, ISO, the EU AI Act, or the OECD, that source is cited. Where a term is used differently across frameworks, the most widely recognized usage is provided. Adversarial Example An input to an AI system that has been deliberately crafted – often through barely perceptible modifications – to cause Read more
We distinguish between confirmed timelines – statutory effective dates, published standards, and announced regulatory actions – and expected or anticipated developments. Where uncertainty exists, it is stated plainly. EU AI Act: Confirmed Milestones The EU AI Act implementation timeline provides the following confirmed compliance milestones: Milestone Confirmed Date Prohibitions on unacceptable-risk AI systems apply 2 February 2025 – Confirmed, in force AI literacy obligation (Article 4) applies 2 February 2025 – Confirmed, in force GPAI Read more
Most AI governance failures are not caused by malice. They are caused by recognizable organizational and structural patterns – recurring failure modes that have been identified and named in the literature. Understanding these anti-patterns is the first step to avoiding or remediating them. This chapter names each one directly, explains its mechanism, and suggests remediation. Ethics Washing Ethics washing is the practice of using the language of responsible AI – publishing principles, appointing ethics boards, Read more
