access-control

A reflection on the challenge of managing permissions for AI agents in production, arguing that inventory alone is insufficient and that teams need unified control over agent actions, with ongoing interviews planned.

This opinion piece argues that many AI agent demos neglect proper security by granting agents broad access to company tools without oversight, comparing it to giving a new employee full access on day one.

Gitolite is a tool for hosting Git repositories on a central server with fine-grained access control and many other powerful features.

Explores the challenge of where to implement authorization when an AI agent can call multiple tools, discussing architectural considerations for secure access control.

The paper proposes a theory of least autonomy as a generalization of least privilege for agentic AI systems, defining compositional blast radius and agent influence graphs to detect authorization composition and cross-domain capability composition.

The user shares how they used Tailscale to configure access control and SSH policy to isolate internal and public servers, preventing lateral spread after a breach. By grouping devices with tags, they restrict public servers from reverse-connecting to personal devices, improving security.

This paper introduces GRAM (gradient-routed auxiliary modules), a modular pretraining method that enables access control by selectively adding and ablating modules to limit dual-use capabilities in AI models, showing cost reductions compared to data filtering.

The article asks how engineers manage permissions for AI agents in production, highlighting common problems with broad access and lack of audit trails.

A discussion about how to give AI agents practical capabilities ('hands') without granting full access or control, exploring safety and management strategies.

A developer discusses challenges in deploying AI agents to production without causing unintended harm, seeking advice on control mechanisms like least privilege, shadow mode, rate limits, and approval workflows.

This article discusses how AI agent demos often succeed while production deployment reveals critical security and authorization issues, emphasizing that model quality does not solve problems like access control, data leaks, and auditability.

The author describes a practical AI agent setup where the agent (Hermes) accesses infrastructure only through an access layer (Teleport) that enforces the human user's identity and permissions, arguing that useful agents must operate within existing permission models rather than having their own god-like access.

A security researcher discovered that registering as a FIFA agent granted access to FIFA's Microsoft Entra tenant, allowing them to bypass client-side authentication and access the live production streaming management panel for the 2026 World Cup, including RTMP stream keys for all matches. The researcher had to contact FIFA, MediaKind, HBS, CISA, and the FBI to get the issue fixed.

GateMem is a benchmark for evaluating memory governance in multi-principal shared-memory agents, covering utility, access control, and forgetting across medical, office, education, and household domains. Current methods fail to balance all three, showing that reliable shared institutional deployment remains elusive.

Cast is an open-source harness for multi-user, multi-agent AI systems that provides config-based access control instead of prompt-based rules, preventing models from leaking or overriding permissions and enabling self-hosted agent teams.

This paper proposes a compositional authorization framework for agentic AI systems, introducing primitives for delegation, scope attenuation, and recursive permission chains to govern autonomous AI agents.

This paper presents the Redpanda Agentic Data Plane (ADP), an architecture that uses out-of-band metadata channels to enforce governance for autonomous AI agents, ensuring safety by keeping security-critical metadata outside agents' data path.

A security design for AI agents accessing production cloud infrastructure using split credentials and approval gates to prevent destructive actions without human approval.

A discussion on whether AI agents should be given direct access to payment systems, weighing convenience against security risks.

This article highlights a critical security vulnerability in AI agents where output execution bypasses proper authority checks, arguing for 'external admission' gates before granting trusted context or secrets.