Audit-Ready Attestation System

• Audit-Ready Attestation Systems are security architectures that produce precise, replayable, and cryptographically protected measurements for rigorous third-party auditing.
• They combine formal layered measurement models with ordered evidence bundling and nested TPM quotes to ensure system integrity and forensic traceability.
• Key design trade-offs include balancing depth vs. latency and heterogeneity vs. isolation, which are essential for regulatory compliance and robust performance.

An audit-ready attestation system is a security architecture that empowers third-party auditors to verify system integrity claims with precise, replayable, and cryptographically protected evidence. Such systems are engineered for environments where strong trust guarantees and forensic traceability are paramount, such as regulated workflows, supply chains, critical infrastructure, or cloud-native platforms. Auditability demands verifiable measurements covering all security-relevant layers, rigorous bundling and ordering of evidence, and open records with appraisal policies and compliance artifacts. Below, the concept is formalized via layered attestation system principles, precise construction steps, and design trade-offs, following the technical framework presented in "Principles of Layered Attestation" (Rowe, 2016).

1. Formal Layered Measurement and Attestation Model

A layered attestation system is modeled as a quintuple $\mathcal A=(O, M, C, P, L)$. Here:

• $O$: Set of system objects/components, including a distinguished root of trust for measurement $\mathsf{rtm}\in O$.
• $M\subseteq O\times O$: Directed acyclic measurement relation; $M(o_1,o_2)$ means object $o_1$ measures (attests to) object $o_2$.
• $C\subseteq O\times O$: Integrity context dependencies; $C(o_1,o_2)$ signifies $o_1$ contributes runtime context for $o_2$.
• $P=T\times R$: Set of PCR registers indexed by TPMs $T$ and PCR indices $R$. Locality $L\subseteq O\times P$ is injective: if $L(o, p)$, then only $o$ extends PCR $p$.

Layered dependencies are defined recursively: $$\begin{aligned} D^1(o) &= M^{-1}(o)\cup C^{-1}(M^{-1}(o)),\ D^{k+1}(o) &= \bigcup_{o'\in D^k(o)} D^1(o'). \end{aligned}$$ Each $D^k(o)$ denotes the $k$th-layer measurers and context providers influencing $o$.

Measurement events ${o_1}\xrightarrow{\cdot} {o_2}$ produce an output $v\in\mathcal{T}_\Sigma(V)$ only if $M(o_1,o_2)$, with formal integrity claims tied to the corruption state $\mathsf{cs}(e,o)\in\{\mathsf{good},\mathsf{bad}\}$ at any event $e$. Measurement accuracy axiom (A1) enforces that an intact measurer and context report $\mathcal G(o)$ iff $\mathsf{cs}(e,o)=\mathsf{good}$.

2. Construction of an Audit-Ready Layered Attestation System

The canonical construction procedure follows these steps:

1. Root-of-Trust Selection: Define a small, hardware-enforced $\mathsf{rtm}$ (usually a TPM). Each direct child $o$ is assigned a unique PCR $p_o$ under $L(o, p_o)$.
2. Measurement Function Specification: For each $o$, construct a deterministic measurement function

$$\mu_o: \textsf{state}(o)\longrightarrow\mathcal{T}_\Sigma(V)$$

guaranteeing precise detection of any illicit state.

1. Dependency Graph Computation: Calculate the full dependency graph $(O, M, C)$; evaluate layer sets $D^1(o),\ldots,D^k(o)$ for all relevant $o$.
2. Bottom-Up Measurement Invariant: Impose strict ordering—each $\mu_o$ runs only after all $\mu_{o'}$ ($o'\in D^1(o)$) have executed. Measurements must be "well-supported" (occur after all dependent context measurements).
3. Bundling and Quotation Chain: Aggregate measurements at each layer in PCRs and issue nested TPM quotes, each signing a fresh nonce and relevant PCR values. Final attestation chains should cryptographically bind every measurement along with the order, context, and nonce-injection events.

Example configuration (minimal assurance): $$O = \{\mathsf{rtm}, A, T\}, \quad M = \{(\mathsf{rtm}, A), (A, T)\}, \quad C = \emptyset$$ Measurement order: $$\mathsf{rtm}\!\to\!A\to A\!\to\!T\to\mathsf{quote}(n,\{p_T\})$$ Assurance level $\alpha$ is achieved if: $\text{difficulty}(A) + \Delta t > \alpha$

3. Trustworthiness, Risk Quantification, and Audit Principles

The "Recent-or-Deep Principle" (Theorem 1) governs the residual trust risks: for any undetected compromise, either a recent re-corruption occurred at a shallow layer ($D^1$), or a deep compromise at $D^2$ or below existed. Quantitative risk is a function of:

• $\Delta t_{\!toctou}$: Time between measurement and final quote.
• $\mathsf{difficulty}(o)$: Cost of corrupting object $o$.

Stronger configurations employ diversity (parallel measurers), at the cost of increased log and PCR size. Each additional layer ($d$) accrues $O(d)$ latency; each additional parallel measurer ($m$) scales PCRs/signatures by $O(m)$. Attacker must either corrupt all shallow measurers in $\Delta t$ or subvert a deeper, more protected level.

Trusted Computing Base (TCB) minimization is paramount: restrict $\mathsf{rtm}$ to minimal hardware, limit $C^{-1}(o)$ (context dependencies), and avoid merging heterogeneous measurers.

4. Failure Detection, Layered Diagnosis, and Automated Remediation

Audit-ready attestation architectures must support on-the-fly failure isolation:

• Periodic self-measurements: every $o$ appends a timestamped measurement every $T_s$ seconds.
• On quote/or policy verification failure:
  • Identify deepest PCR evidencing compromise.
  • Re-attest all components from $D^1(o_t)$ upward.
  • Apply containment and repair procedures at the lowest failing layer.

Audit remediation is typically automated for compliance—fallback onto diagnosis, execution of repair routines, and regeneration of evidential chains.

5. Evidence Records, Audit Logs, and Compliance Reporting

Open, verifiable evidence records are central:

• Standard quote formats (TPM 2.0, IETF RATS) encapsulate everything needed for compliance/certification.
• Complete, ordered chains of nested quotes, with explicit metadata: PCR mapping, nonce provenance, measurement policies.
• Public repository for measurement source code and reproducible build artifacts strengthens audit integrity.
• Machine-readable policies (JSON/XML) define the acceptability of PCR values; open-source verification tools automate compliance checks.

Append-only, tamper-evident logs of all extend and quote events are digitally signed and streamable (REST APIs) for third-party auditing. Each compliance report documents dependencies, measurement order, nonce window, and adversary-effort estimates.

6. Implications, Design Trade-offs, and Deployment Considerations

There are key architectural trade-offs:

• Depth vs. assurance vs. latency: Deeper, more isolated layers provide stronger guarantees at a direct latency cost.
• Heterogeneity vs. isolation: Isolating distinct measurers (dedicated PCR/locality) increases log size but prevents cross-domain trust dilution.
• Granularity: Fine-grained measurement functions increase detection power but may impact system performance.
• Automated reporting: Full adherence to audit-readiness requires periodic log extraction, pickled attestation chains, signed compliance artifacts, and open policy exposure.

A plausible implication is that adherence to these principles is required for regulatory audit readiness in environments governed by frameworks such as the EU AI Act, NIST SP 800-92, or other high-assurance standards.

In sum, audit-ready attestation systems built under the formal framework and principles of layered attestation (Rowe, 2016) provide rigorous, cryptographically verifiable, and replayable measurement chains, which are essential for trustworthy, forensically analyzable integrity validation in modern multi-layered computing environments.