{"id":"ec7c5aba-41f0-470a-a8ae-ca298d316672","arxiv_id":"2606.21129","paper_version":1,"verdict":"UNVERDICTED","confidence":"LOW","novelty_score":5.0,"correctness_risk":"unknown","formal_verification":"none","parameter_count":0,"one_line_summary":"AgenticOS proposes a four-layer architecture (Ghost Kernel, Logic Shutter, Agent Capsule, Semantic Boundary Gateway) plus Intent ABI and Manifest-Only Runtime to enforce least-privilege from structured agent intent declarations.","lead":"The paper proposes AgenticOS, an intent-oriented secure OS architecture that turns the OS into an intent filter for autonomous AI agents instead of a resource manager. A smart generalist might read it to understand a proposed way to contain security risks from LLM agents that plan, use tools, and execute code.","discovery_kind":"new_method","skeptic_critique":{"model":"grok-4.3","headline":"Core claim rests on unshown ability to synthesize gap-free least-privilege environments from agent-submitted intents","rationale":"The load-bearing concern is identical to the reader's weakest_assumption; the abstract-only basis already yields UNVERDICTED, so the same point does not alter the verdict.","tokens_in":1698,"tokens_out":297,"duration_ms":14012,"concrete_test":"Construct a minimal formal model of the Intent ABI and Manifest-Only Runtime (e.g., in TLA+ or Alloy); encode a prompt-injection scenario that produces a malicious but syntactically valid intent declaration; check whether any generated capability set still permits an unauthorized information flow. If a violating trace exists, the synthesis claim is incomplete.","verdict_should_be":"UNCHANGED","load_bearing_attack":"The central claim requires that (a) agents reliably emit accurate structured intent declarations even after prompt injection or tool compromise, and (b) the OS (via Intent ABI, Manifest-Only Runtime, Weaver generation, and the four named layers) can derive and enforce a complete least-privilege set that blocks all unauthorized compositions of POSIX primitives. The abstract asserts this reframing solves the structural problem but supplies neither a formal model of intent-to-privilege mapping nor an argument that the synthesis is sound (i.e., that every possible attack path is covered by the generated constraints). Without that, the architecture names components but does not demonstrate the required property.","agreement_with_reader":"agree"},"referee_report":{"model":"grok-4.3","summary":"The paper proposes AgenticOS, an intent-oriented secure OS architecture for LLM-driven autonomous agents. It argues that traditional resource-exposure-plus-permission-check models fail when agents are compromised via prompt injection or malicious tools, allowing unauthorized composition of POSIX primitives. The core reframing is to treat the OS as an 'intent filter': agents submit structured intent declarations from which the system synthesizes least-privilege environments enforced via mandatory mediation, auditing, and information-flow constraints. The design introduces a four-layer architecture (Ghost Kernel, Logic Shutter, Agent Capsule, Semantic Boundary Gateway) together with an Intent ABI, Manifest-Only Runtime, Weaver-based capability generation, and an admission model for AgenticOS-native Skills.","tokens_in":1827,"tokens_out":581,"duration_ms":20407,"significance":"If the proposed intent-to-privilege synthesis can be shown to be sound and complete, the architecture would offer a substantive advance in securing agentic systems by shifting enforcement from low-level resource permissions to high-level, auditable intent mediation. The consolidation of delegable capabilities into OS-native mechanisms is a coherent direction that could influence future designs for AI agent runtimes.","major_comments":[{"comment":"Abstract (core insight paragraph): the claim that intent declarations enable synthesis of a 'least-privilege environment' that blocks all unauthorized compositions of POSIX primitives is unsupported by any formal model of the intent language, mapping rules, or completeness argument showing that every attack path is covered by the generated constraints.","section":"Abstract"},{"comment":"Four-layer architecture and implementation components: the roles of Ghost Kernel, Logic Shutter, Agent Capsule, Semantic Boundary Gateway, Intent ABI, Manifest-Only Runtime, and Weaver generation are described at a naming level only, with no specification of how these layers derive or enforce constraints that remain gap-free after agent compromise.","section":"Four-layer architecture description"},{"comment":"Admission model and Skills section: no argument or example is given that the system can still produce correct least-privilege sets when submitted intents are inaccurate (the weakest assumption identified in the design), nor is there discussion of fallback mediation when intent accuracy cannot be guaranteed.","section":"Admission model for AgenticOS-native Skills"}],"minor_comments":[{"comment":"The manuscript introduces multiple novel terms (Ghost Kernel, Logic Shutter, Agent Capsule, Semantic Boundary Gateway, Weaver) without relating them to prior OS or capability-system literature, which reduces accessibility.","section":"Terminology"}],"recommendation":"major_revision","confidential_remarks":"The submission is a high-level architectural proposal without implementation, prototype, formalization, or evaluation; this may place it outside the typical scope of a journal that expects substantiated security results rather than vision statements."},"author_rebuttal":{"model":"grok-4.3","summary":"We thank the referee for the constructive and precise comments. The manuscript is an initial architectural proposal rather than a formally verified system, and we agree that several claims require qualification and that additional detail and discussion of limitations are needed. We address each major comment below and will incorporate the suggested changes in the revised version.","responses":[{"response":"We agree that the abstract overstates the current support for the claim. The paper presents a conceptual architecture without a formal model or completeness argument. We will revise the abstract to state that the design 'aims to' synthesize least-privilege environments and will add a short subsection in the discussion section outlining the requirements for a formal intent language together with a note that completeness arguments remain future work.","revision_made":"yes","referee_comment":"[Abstract] Abstract (core insight paragraph): the claim that intent declarations enable synthesis of a 'least-privilege environment' that blocks all unauthorized compositions of POSIX primitives is unsupported by any formal model of the intent language, mapping rules, or completeness argument showing that every attack path is covered by the generated constraints."},{"response":"The referee correctly observes that the layer descriptions remain high-level. We will expand the architecture section with additional paragraphs and a figure that illustrate the information-flow and mediation steps performed by each layer. We will also add an explicit limitations paragraph stating that gap-free enforcement after compromise has not been formally shown and would require implementation-level verification.","revision_made":"yes","referee_comment":"[Four-layer architecture description] Four-layer architecture and implementation components: the roles of Ghost Kernel, Logic Shutter, Agent Capsule, Semantic Boundary Gateway, Intent ABI, Manifest-Only Runtime, and Weaver generation are described at a naming level only, with no specification of how these layers derive or enforce constraints that remain gap-free after agent compromise."},{"response":"We acknowledge the absence of this discussion. We will insert a new paragraph in the admission-model section that states the accuracy assumption, gives an example of how an inaccurate intent could produce an over- or under-privileged set, and describes two fallback mechanisms: (1) conservative default privilege synthesis and (2) optional human review for high-risk actions.","revision_made":"yes","referee_comment":"[Admission model for AgenticOS-native Skills] Admission model and Skills section: no argument or example is given that the system can still produce correct least-privilege sets when submitted intents are inaccurate (the weakest assumption identified in the design), nor is there discussion of fallback mediation when intent accuracy cannot be guaranteed."}],"tokens_in":1443,"tokens_out":554,"duration_ms":13562,"standing_objections":[]},"desk_editor":{"model":"grok-4.3","letter":"The paper's main point is a four-layer design that turns the OS into an intent filter: agents submit structured declarations instead of raw resource requests, and the system is supposed to generate a mediated, auditable execution environment from them. The authors name the layers Ghost Kernel, Logic Shutter, Agent Capsule, and Semantic Boundary Gateway, plus an Intent ABI, Manifest-Only Runtime, and Weaver-based capability generation.\n\nThe write-up does a straightforward job stating the problem. Traditional permission checks on POSIX primitives can be composed by a compromised agent into actions that exceed the original task, and the proposal tries to cut that off at the intent level rather than after the fact.\n\nThe concrete layering and component names are new relative to the abstract, even if the general idea of capability or intent-driven restrictions has older precedents. That is the extent of what is actually delivered.\n\nThe central difficulty is that the architecture assumes two things without support: that agents will emit accurate structured intents even under prompt injection or tool compromise, and that the OS can derive and enforce a complete set of constraints that blocks every unauthorized composition. No formal mapping from intent to privileges is given, no argument is made that the generated constraints are exhaustive, and there is no implementation or test to check whether the named pieces achieve the claimed property.\n\nThis is early-stage work aimed at people already thinking about OS-level protections for autonomous agents. A reader looking for mechanisms that have been shown to work or for a rigorous security argument will not find them. It does not yet contain enough substance to justify sending it to referees.","headline":"AgenticOS sketches an intent-filter OS architecture for AI agents but supplies no model or evidence that the synthesis step actually produces gap-free least-privilege environments.","tokens_in":2307,"tokens_out":395,"would_cite":false,"duration_ms":16864,"reading_group":"maybe","serious_thinker":"yes","would_accept_peer_review":false},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":[],"model":"grok-4.3","headline":"AgenticOS turns the OS into an intent filter that builds least-privilege environments from agent declarations rather than exposing raw resources.","keywords":["operating system security","AI agents","intent-based access control","least privilege enforcement","autonomous agents","prompt injection defense","secure architecture","capability synthesis"],"falsifier":"An experiment in which a compromised agent submits a benign intent yet still reaches unauthorized resources or performs actions outside the synthesized environment after receiving malicious tool output.","tokens_in":2615,"feed_emoji":"🛡️","tokens_out":627,"duration_ms":13234,"temperature":0.7,"pith_summary":"The paper proposes that autonomous AI agents should not request low-level resources directly because compromise through prompt injection or bad tool outputs lets attackers chain standard OS calls into unauthorized actions. Instead, agents submit structured intent declarations, and the operating system synthesizes a constrained execution environment that includes mandatory mediation, auditing, and information-flow rules. This shifts the OS role from resource manager to intent filter while still allowing existing applications to run. A reader would care because current permission models on exposed primitives cannot contain capable planning agents once the runtime is subverted.","feed_headline":"OS reframes as intent filter for AI agents","feed_subtitle":"Agents declare structured goals; the system builds constrained environments with mediation and auditing instead of granting direct resource","key_machinery":"The intent filter that synthesizes least-privilege environments from structured intent declarations using a four-layer architecture and Intent ABI.","core_discovery":"AgenticOS reframes the OS from a resource manager into an intent filter: agents submit structured intent declarations from which the system synthesizes a least-privilege environment with mandatory mediation, auditing, and information-flow constraints. The architecture implements this through a four-layer design consisting of Ghost Kernel, Logic Shutter, Agent Capsule, and Semantic Boundary Gateway, together with the Intent ABI, Manifest-Only Runtime, Weaver-based capability generation, and an admission model for native Skills. The approach consolidates delegable auditable capabilities into OS-native forms without replacing all applications.","pith_inferences":["The design could limit the damage from prompt injection by restricting what behaviors can be composed from any single intent.","It might support multi-agent coordination if intents can be negotiated or composed across capsules.","Real-world validation would require testing whether synthesis misses attack paths in complex tool-use scenarios."],"forward_implications":["Auditing and mediation become mandatory at the level of declared intents rather than raw resource accesses.","Information-flow constraints are enforced automatically from the intent declarations.","Existing applications continue to run while agent runtimes receive OS-native capabilities.","Skills are admitted through a model that integrates directly with the intent synthesis process."],"fun_headline_variants":["AgenticOS reframes OS as intent filter for agents","Agents declare intents for mediated OS environments","Secure OS architecture uses intent ABI for AI agents","Least-privilege environments from agent intent declarations"],"cache_read_input_tokens":2112,"weakest_assumption_plain":"Agents will reliably submit accurate structured intent declarations and the OS can correctly synthesize and enforce a least-privilege environment without missing attack paths.","fun_headline_variants_meta":{"raw":{"variants":["AgenticOS reframes OS as intent filter for agents","Agents declare intents for mediated OS environments","Secure OS architecture uses intent ABI for AI agents","Least-privilege environments from agent intent declarations"]},"model":"grok-4.3","cost_usd":0.00959,"raw_usage":{"total_tokens":4279,"prompt_tokens":671,"num_sources_used":0,"completion_tokens":56,"cost_in_usd_ticks":95899500,"prompt_tokens_details":{"text_tokens":671,"audio_tokens":0,"image_tokens":0,"cached_tokens":256},"completion_tokens_details":{"audio_tokens":0,"reasoning_tokens":3552,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"tokens_in":671,"tokens_out":56,"duration_ms":24733,"temperature":1.0,"reasoning_tokens":3552,"cache_read_input_tokens":256,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-06-26T13:54:46.761056+00:00","model_set":{"reader":"grok-4.3"},"falsifier":"An experiment in which a compromised agent submits a benign intent yet still reaches unauthorized resources or performs actions outside the synthesized environment after receiving malicious tool output.","supporting_citations":[],"review_version":1}