Agent Security, Tool Sandboxing, and Permission Boundary Literature Audit Plan
Structure an exhaustive literature review plan assessing runtime tool sandboxing, prompt-to-tool injection vulnerabilities, and least-privilege controls.
Use this template when planning an academic and industrial literature audit focused on agentic security boundaries, malicious tool invocation, least-privilege containment, and safe dynamic execution environments. Ideal for AI safety researchers and security architects.
Role: Senior AI Safety & Tool Sandboxing Research Lead specializing in secure runtime environments and autonomous agent threat modeling.
Context
- Primary Threat Vector: {{threat_vector_focus}}
- Sandboxing Infrastructure: {{sandboxing_environment}}
- Privilege Escalation Models: {{privilege_escalation_models}}
- Target Regulatory and Compliance Standards: {{compliance_framework}}
- Literature Publication Window: {{publication_window}}
- Final Synthesis Deliverable: {{synthesis_deliverable_format}}
Task
Formulate a rigorous, step-by-step literature audit and review plan to identify, classify, and evaluate published research on agentic tool containment, indirect injection mitigation, and runtime authorization models against {{threat_vector_focus}}.
Method
- Define security-specific literature search keywords targeting prompt-to-tool injection, sandbox breakouts, and unauthorized API traversal.
- Filter discovered publications across {{publication_window}} against strict empirical criteria (e.g., demonstrated PoC exploits, verified runtime mitigations).
- Establish an audit taxonomy categorizing isolation models: kernel namespaces, WebAssembly micro-sandboxes, eBPF probes, and hypervisor VMs.
- Design a risk-scoring extraction template to evaluate the rigor of reported mitigations against {{privilege_escalation_models}}.
- Compare academic findings on dynamic human-in-the-loop (HITL) approval gates against fully autonomous authorization protocols in {{sandboxing_environment}}.
- Align extracted mitigation patterns against mandatory control standards specified in {{compliance_framework}}.
- Map literature-backed defensive blind spots where current tool-calling validation engines fail to neutralize adversarial payloads.
- Structure the project schedule, synthesis phases, and peer-review milestones into {{synthesis_deliverable_format}}.
Constraints
- Focus exclusively on security boundaries between LLM output parsing, tool schema execution, and OS-level runtime isolation.
- MUST evaluate both software-based containerization and formal capability-based security models.
- MUST NOT accept theoretical safety papers that lack practical evaluation on realistic API execution environments.
- All evaluated defense architectures must map to requirements in {{compliance_framework}}.
Output format
- Audit Plan Scope and Hypotheses: 200 words covering threat models and research scope.
- Methodological Review Pipeline: 5-step operational workflow with validation criteria for each paper inclusion.
- Threat-Defense Literature Taxonomy: Structured template for classifying papers across attack surfaces and sandbox tiers.
- Deliverable Milestones & Audit Timeline: Weekly milestone plan with review deliverables concluding in {{synthesis_deliverable_format}}.
Self-review
- Are the security evaluation criteria directly focused on tool-calling vulnerabilities and sandbox breakouts?
- Does the plan address compliance mapping against {{compliance_framework}}?
- Are both software-level isolation and API privilege management evaluated throughout the method?
Explicit role, a named task, and discrete steps the model can follow.
Background, inputs and variables the model needs before it starts.
Hard boundaries — what the model must and must not do.
A named, field-level shape for the response.
Ordered work items that force analysis before an answer.
Length and structure that travel across frontier models.
Signal density — instruction weight without padding.
Documented variables so the scaffold adapts to new inputs.
Quality bar, assumptions and behaviour when inputs are thin.
How much real usage the template has behind it.