Remote Attestation Agent (RAA)

• Remote Attestation Agent (RAA) is a trusted module that collects, protects, and exports cryptographically signed evidence of a system’s integrity, state, and execution flows.
• RAA designs span software, hardware, and hybrid models, leveraging components like TPMs, ARM TrustZone, and Intel SGX to ensure isolation and secure key management.
• RAAs underpin attestation protocols in IoT, cloud, edge, and TEE-enabled platforms, enabling runtime and control-flow attestation while addressing scalability and security challenges.

A Remote Attestation Agent (RAA) is the trusted software and/or hardware module within a computing platform that collects, protects, and exports evidence regarding the system’s software or execution state for verification by a remote party. RAAs are foundational in attestation protocols across embedded systems, IoT, cloud/edge servers, confidential web services, and TEE-enabled platforms, providing the cryptographic basis for integrity, authenticity, and, in advanced cases, runtime and control-flow attestation (Banks et al., 2021).

1. Architectural Models and RAA Placement

RAAs are instantiated in several attestation paradigms: software-based, hardware-based, and hybrid models. In software-based RA, the agent is a minimal measurement engine and cryptographic library executing under a commodity OS, with security derived from protocol-level assumptions (e.g., timing variance, or minimal trust in the boot ROM) (Banks et al., 2021). Hardware-based RAAs leverage secure hardware components such as TPMs, ARM TrustZone, Intel SGX, or Physically Unclonable Functions (PUF) to guarantee exclusive access to secrets, atomic execution, and isolation (Nunes et al., 2018, Eldefrawy et al., 2017, Zhang et al., 14 Feb 2024). Hybrid designs co-design minimal dedicated hardware trust anchors with a lightweight software stack, formally verifying properties such as exclusive key access, atomicity, and controlled invocation (notably in VRASED, TrustLite, SANCUS, HYDRA, and many recent cloud TEE systems) (Nunes et al., 2018, Eldefrawy et al., 2017, Banks et al., 2021).

RAA deployment may occur as kernel-space modules (ScaRR’s control-flow RAA (Toffalini et al., 2018)), as user-space trusted processes with microkernel-enforced separation (HYDRA’s seL4-based RAA (Eldefrawy et al., 2017)), in enclave- or TEE-resident services (Sentinel, JANUS, HTTPA, RA-WEBs (Zhang et al., 30 Aug 2025, Zhang et al., 14 Feb 2024, King et al., 2021, Akama et al., 2 Nov 2024)), as statically linked pseudo-Trusted Applications (PDRIMA (Mao et al., 6 Dec 2025)), or as minimal passport-style agents for constrained devices (Moustafa et al., 2023). Design choices must reflect attack surface, performance, and trust boundary required by the use case.

2. Measurement and Evidence Generation

The RAA’s core function is to measure specified aspects of system integrity—memory regions, code identity, runtime execution paths, or even control-flow traces—and cryptographically bind these to an attestation request such as a nonce or challenge (Banks et al., 2021). The classical measurement operation is a hash or MAC of the target region (M = H(IMG ∥ nonce)), encoded as part of a challenge-response protocol.

Advanced RAAs frequently extend this to runtime or behavioral evidence. In ScaRR, the agent segments execution into sub-paths between registerable checkpoints, hashes ordered lists of significant control-flow transitions (LoA), and emits measurements keyed by checkpoint pairs and edge-hash (M = (CP_A, CP_B, H(LoA))) (Toffalini et al., 2018). Control-flow attestation (CFA) RAAs such as C-FLAT, ACFA, and Sentinel perform continuous logging of executed branches or call/return edges, building hash chains over execution events or authenticated logs that can be linearly or periodically verified (Caulfield et al., 2023, Zhang et al., 30 Aug 2025). When data integrity is required, Sentinel further tracks critical model variables and their update constraints during local training for federated machine learning, logging both $\mathcal{CF}_i$ (control flow) and $\mathcal{CV}_i$ (critical variables), and signing the resulting evidence with a TEE-protected asymmetric key (Zhang et al., 30 Aug 2025).

Policy-driven and modular RAAs (PDRIMA, JANUS) support extensible measurement selection via policy tables, appraised measurement logs, and dynamically maintained hash chains or Merkle roots over variable evidence sets (Mao et al., 6 Dec 2025, Zhang et al., 14 Feb 2024).

3. Protocol Flow and Cryptographic Workflows

Standard RAA-driven attestation follows a challenge–response protocol: the remote verifier issues a random nonce; the RAA computes a measurement, often as a hash or MAC/signature over the measured state concatenated with the nonce; finally, the RAA returns this evidence and authentication tag (Banks et al., 2021). Cryptographic primitives include:

• HMAC or MAC over measurements for constrained devices or symmetric deployments (Nunes et al., 2018, Dave et al., 2021, Eldefrawy et al., 2017).
• Public key signatures (SK_Attest, sgx_quote) in asymmetric or TEE-enabled protocols, with X.509 or TEE-specific certificate chains as identity binders (King et al., 2021, Akama et al., 2 Nov 2024, Mao et al., 6 Dec 2025).
• Authenticated encryption for privacy or multi-principal protocols (symmetric senc/adec, AEAD for PUF-based flows in JANUS) (Zhang et al., 14 Feb 2024, Moustafa et al., 2023).
• Hash chains, PCR extension logic, or Merkle forest roots for tamper-evident accumulation of streamed or event-based measurements (Mao et al., 6 Dec 2025, Akama et al., 2 Nov 2024).

Protocols may range from classic 2-message flows (Verifier: AttestReq; RAA: AttestResp), to multi-phase systems for federated learning (Sentinel), passport attestation for symmetric-only relying parties (APCR-LPM (Moustafa et al., 2023)), and multi-step (provisioning, verification, monitoring) integrations in confidential web (RA-WEBs, HTTPA (Akama et al., 2 Nov 2024, King et al., 2021)). Some contexts involve continuous report streaming and real-time integrity checks, with compressible, batched evidence formats (ScaRR (Toffalini et al., 2018)).

4. Isolation, Trust Anchors, and Formal Security Properties

Isolation of the RAA, and the secrets it holds, is achieved via diverse means. Microkernel-based approaches (seL4 in HYDRA) leverage formally proven capability systems and scheduling to guarantee that the RAA’s code, attestation key, and address space are accessible only to the RAA thread while maintaining real-time preemption safety (Eldefrawy et al., 2017). Hardware/Software co-designs instrument the hardware to enforce exclusive access privileges (VRASED: PC-range + DMA gating for attestation key and stack; ACFA: non-masked NMI and bus-monitor logic), permitting formal specifications in LTL (Nunes et al., 2018, Caulfield et al., 2023). TEE- or enclave-based architectures guarantee isolation via hardware partitioning and cryptographic boundaries (SGX, ARM TrustZone, OP-TEE (Mao et al., 6 Dec 2025, Zhang et al., 30 Aug 2025, King et al., 2021, Akama et al., 2 Nov 2024)).

Security goals are formally stated, often as conjunctions of:

• Integrity: No adversary can forge an attestation report for an unmeasured or modified state.
• Freshness: Each attestation binds to a unique, unpredictable challenge (nonce, timestamp).
• Authenticity: Only the RAA possessing protected secrets can produce valid tags.
• Confidentiality: Secrets (keys, measurements) remain undisclosed to adversaries.
• Atomicity: The measurement/report is computed as an indivisible block—no partial execution, no mid-flight modification.
• Controlled invocation: Only authorized entry-points trigger the RAA logic.

For instance, VRASED proves invariants such as “whenever attestation code executes, no other code can read K until attestation finishes” in LTL. Multiple frameworks (VRASED, HYDRA, OPERA, SeED) apply symbolic or model-checked proofs over both hardware and protocol (Nunes et al., 2018, Eldefrawy et al., 2017, Banks et al., 2021).

5. Performance, Scalability, and Practical Challenges

Performance and overheads vary across designs but are rigorously characterized. Attestation latency and throughput are typically dominated by cryptographic operations (MAC, signature), memory mapping, and logging. For example:

• ScaRR validates up to 2×10⁶ control-flow measurements/s (verifier-side on Intel i7) and generates up to 4.3×10⁵/s (prover-side on SPEC benchmarks), outperforming embedded RA protocols by orders of magnitude (Toffalini et al., 2018).
• HYDRA attests 10 MB in <500 ms on typical ARM-class SoCs; mapping memory regions remains <20% of total overhead (Eldefrawy et al., 2017).
• SRACARE (hybrid RA + recovery) achieves under 8% boot and run-time overhead, with FPGA HMAC outperforming software by roughly 10× (Dave et al., 2021).
• Sentinel incurs 5–10% additional runtime during federated learning training (ARM Cortex), with report generation and verification scaling linearly in event and client count (Zhang et al., 30 Aug 2025).
• ACFA (hardware CFA) imposes zero per-instruction overhead (logged in hardware), with end-to-end collection and reporting per slice (≈650 ms at 6000 CF events) (Caulfield et al., 2023).

Communication and network overheads (particularly for streaming attestation) are mitigated via batched proofs, compression (ScaRR, RA-WEBs), and adaptive reporting intervals.

6. Advanced Use Cases: Support for Control-Flow Attestation, Swarm, and Resilience

Modern RAAs extend beyond simple binary or memory attestation to address execution semantics (runtime attestation), collective evidence aggregation (swarm attestation), policy-driven measurements, and in some cases, active remediation (Toffalini et al., 2018, Caulfield et al., 2023, Zhang et al., 14 Feb 2024).

Control-Flow Attestation (CFA) is implemented either via compiler instrumentation (C-FLAT, ScaRR, Sentinel) or via on-bus monitoring (ACFA). These approaches capture the precise sequence of execution events and expose them—directly (raw logs) or via hash chains—to the remote verifier, enabling detection of code-reuse, ROP/JOP, data-only, and advanced hijacking attacks (Caulfield et al., 2023, Zhang et al., 30 Aug 2025, Toffalini et al., 2018).

Swarm attestation protocols coordinate hundreds or thousands of RAAs for distributed attestation, leveraging aggregation (MAC-based, Schnorr multi-sig, consensus) and supporting dynamic topologies (Banks et al., 2021).

Resilience to attacks is addressed in systems such as SRACARE (onboard rollback recovery), ACFA (hardware-enforced remediation triggers), and PDRIMA (policy-driven re-measurement and audit logs) (Dave et al., 2021, Caulfield et al., 2023, Mao et al., 6 Dec 2025). A plausible implication is that future RAAs will increasingly integrate policy extensibility, real-time enforcement, and distributed verification for trust in evolving threat landscapes.

7. Best Practices, Limitations, and Future Directions

Current best practices for RAA design include minimizing the trusted code base (RAA logic in ROM or within smallest feasible TCB), strict atomicity and single-entry execution, hardware-enforced key protection and access control, formal specification and verification (LTL, ProVerif, symbolic), cryptographically bound freshness (nonces, timestamps), and extensibility for emerging measurement paradigms (Banks et al., 2021, Nunes et al., 2018).

Limitations identified in the field: reliance on pre-shared secrets or trusted provisioning (Moustafa et al., 2023), physical attack/fault tolerance (most designs, except those explicitly assuming side-channel resistance), network or storage scalability for large logs, and the completeness of reference measurement frameworks (PDRIMA, ScaRR).

Research continues toward resilient decentralized attestation (PUF/smart-contract as in JANUS), seamless web-application CA integration (RA-WEBs, HTTPA), context-aware measurement (Sentinel), and bridging between extremely resource-constrained RPs and full-stack RAAs (passport models) (Zhang et al., 14 Feb 2024, Akama et al., 2 Nov 2024, King et al., 2021, Moustafa et al., 2023, Zhang et al., 30 Aug 2025).

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References:

• "Remote Attestation: A Literature Review" (Banks et al., 2021)
• "ScaRR: Scalable Runtime Remote Attestation for Complex Systems" (Toffalini et al., 2018)
• "Formally Verified Hardware/Software Co-Design for Remote Attestation" (Nunes et al., 2018)
• "HYDRA: HYbrid Design for Remote Attestation (Using a Formally Verified Microkernel)" (Eldefrawy et al., 2017)
• "PDRIMA: A Policy-Driven Runtime Integrity Measurement and Attestation Approach for ARM TrustZone-based TEE" (Mao et al., 6 Dec 2025)
• "RA-WEBs: Remote Attestation for WEB services" (Akama et al., 2 Nov 2024)
• "Teamwork Makes TEE Work: Open and Resilient Remote Attestation on Decentralized Trust" (Zhang et al., 14 Feb 2024)
• "Sentinel: Enabling Trustworthy Federated Learning via Remote Attestation for Mitigating Byzantine Threats" (Zhang et al., 30 Aug 2025)
• "Attestation with Constrained Relying Party" (Moustafa et al., 2023)
• "HTTPA: HTTPS Attestable Protocol" (King et al., 2021)
• "SRACARE: Secure Remote Attestation with Code Authentication and Resilience Engine" (Dave et al., 2021)
• "ACFA: Secure Runtime Auditing & Guaranteed Device Healing via Active Control Flow Attestation" (Caulfield et al., 2023)