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Johannes Brüderl

Publications and source records attributed to Johannes Brüderl.

2 recordsLinked to original sources

If Agents Were Angels, No Governance Would Be Necessary: Out-of-Band Policy Enforcement at a Trusted Tool Boundary

Give an agent a human's credential and it inherits the person's reach without the judgment that limits its use. It can sweep every reachable record into model context, where hidden instructions steer its next call, and every request stays credential-valid while the agent exceeds its job or absorbs a secret. Prompts are a brittle guardrail: one fallible reasoner interprets the task and enforces its limits. We present Out-of-Band Policy Enforcement (OBPE), a trusted boundary outside agent reasoning. It authorizes the typed operation and resource, narrows the query before the backend call, then filters records and fields or masks values in the response. Semantic gating can deny or hold an authorized call on argument values or external state. A data policy owner sets the maximum grant; agent policy can only narrow it. We prove, under stated conditions, that the policy plan is order-independent and agent policy cannot widen the ceiling. Field removal covers one execution; masking and history rules claim less. We release an HTTP proxy prototype simplified from our production system, with conformance tests tying its typed Cedar policy core to the model. Against Jira and ServiceNow mocks, our benchmark compares prompted agents with and without OBPE on four models, including 20 adaptive red-team tasks. A trace failure means protected data entered agent context, an exact value appeared in the answer, or a forbidden effect completed. In 3,621 trials it fell from 57.6% to 0.2%, a cluster-weighted reduction of 41.2 points [95% CI: 27.7, 54.9]; fulfillment fell from 79.1% to 60.9%, while paired safe-useful completion rose 21.8 points [9.5, 35.2]. Some answers reconstructed a value that never entered context or used filtered row counts as an oracle: shaping one execution is not noninterference. Write controls, durable approval, and temporal and aggregate policies lie outside this evaluation.

cs.AI↗

The Importance of Out-of-Band Metadata for Safe Autonomous Agents: The Redpanda Agentic Data Plane

AI agents are increasingly expected to operate as digital employees: accessing enterprise data, making decisions, and taking actions autonomously. But agents are simultaneously less predictable than humans -- prone to hallucination, misinterpretation, and adversarial manipulation -- and more technically capable: with deep system knowledge and high-throughput interfaces cascading damage at machine speed. This combination makes it unsafe to rely on agents to faithfully interpret or propagate security-critical metadata such as access policies, data classifications, and behavioral constraints. We present the Redpanda Agentic Data Plane (ADP), an architecture built around out-of-band metadata channels: infrastructure pathways that carry security context, policy signals, and audit trails deterministically, entirely outside the agent's read and write path and across heterogeneous infrastructure. These channels enforce governance at every stage of the agent lifecycle -- scoping data access on the way in, constraining actions during execution, and capturing tamper-proof transcripts on the way out. We demonstrate ADP with a multi-agent portfolio rebalancing system in which autonomous agents monitor markets, make trade decisions, and execute orders across isolated client accounts -- with per-client data scoping, trade approval thresholds, and tamper-proof audit trails all enforced by out-of-band channels the agents can neither see nor bypass.

cs.AI↗