An extended model for electronic component and module assurance in high-reliability, high-consequence applications

Executive thesis
Electronic parts assurance has historically focused on open-market, or grey-market, procurement where parts lack traceability to the original component manufacturer. That focus remains one of the highest priorities in electronics assurance, but it no longer covers the full threat surface. For high-reliability, high-consequence applications, trust must move from inherited status – brand, paperwork, channel, or authorized status – to verified evidence of provenance, integrity, functionality, and cyber-physical behavior.

This is consistent with the Department of Defense’s public move from the legacy trusted-foundry model toward zero-trust and quantifiable assurance for microelectronics. DoD’s core point is directly transferable to broader electronics assurance: components should not be assumed safe because they appear to come from a trusted position; they should be validated before use [14]-[16].

The legacy model is necessary, but no longer sufficient

The traditional assurance model starts with a sound premise: the highest counterfeit and quality risks often occur when parts are sourced outside traceable original-manufacturer or authorized channels. Standards such as SAE AS6081 and SAE AS6171 remain important because they address independent distribution and test methods for parts with weak or unknown chain of custody [2], [3]. Open-market purchases of obsolete parts remain a significant risk, with issues such as reclaimed components, mixed lots, refinished leads, and altered date codes.

Today the problem has expanded: traceability paperwork can be accurately forged, compromised products can be produced by licensed third parties, franchised distribution can be infiltrated, clones can be manufactured at industrial scale, and genuine manufacturer products or modules can still contain hidden or malicious functionality. The question is no longer only whether a part came from the grey market; it is whether the component, module, documentation, manufacturing & distribution path, configuration, and functionality can be trusted in a high-consequence system.

SAE AS5553 treats counterfeit mitigation as a risk-based supply-chain discipline for organizations that procure and integrate EEE parts, while SAE AS6496 shows that even authorized distribution requires controls for authorization scope, traceability, returns, scrap, and inventory. Together with DFARS electronic-parts clauses, they reinforce the same principle: channel status is important, but it is not a substitute for evidence [17]-[20].

This paper is not arguing that all electronic parts, or all authorized-channel purchases, should receive the same level of testing applied to non-franchise or open-market material. Existing counterfeit-detection and authenticity frameworks remain necessary for non-franchise distributor purchases and should continue to serve as the baseline for that sourcing path. The additional point is that source channel alone should not be treated as conclusive proof of trust. For high-consequence applications, the assurance burden should increase when risk factors such as weak traceability, product complexity, programmability, connectivity, licensed or private-label manufacturing, high-risk jurisdictional exposure, obsolescence, or unexplained anomalies justify additional evidence.

Pillar one: The threat horizon has expanded

Documentation and channel fraud are now supply-chain-level risks. The recent AOG Technics case showed how persuasive paperwork can defeat routine controls: the UK Serious Fraud Office stated that AOG Technics sold more than 60,000 aircraft engine parts accompanied by forged Authorized Release Certificates between January 2019 and July 2023 [4]. In electronic components, the analogous risk is certificates of conformity, authorized-distributor paperwork, lot records, test reports, packaging labels, and chain-of-custody documents that appear authentic but are not independently verifiable.

Counterfeit evolution has expanded to include increasingly complex clones such as interface devices, nonvolatile memory, microcontrollers, configuration devices, and FPGAs marketed as compatible substitutes. A clone may be promoted as a drop-in replacement while failing to match the original design, process, configuration behavior, endurance, environmental limits, or long-term reliability profile. Those same devices can also become cyber-physical attack doorways and surfaces.

Licensing and private-label manufacturing can further obscure control. In the 2024 pager attack attributed in public reporting to Israel, Gold Apollo, the OEM, said that AR-924 pagers bearing its brand were produced and sold by BAC Consulting under brand authorization and that Gold Apollo had no involvement in their design or manufacture [6]. Reuters-based reporting cited by Sky News said the pagers were modified at the production level before detonation [7]. Regardless of the operational details, the supply-chain lesson is that brand authorization and licensing do not guarantee the pedigree, quality, and configuration of a product.

State-influenced manufacturing adds another layer of concern. Reuters-based reporting on Chinese-made power inverters described undisclosed communication devices in some equipment that could create undocumented remote communication channels [8]. Separately, some jurisdictions impose legal obligations on organizations and citizens to support or cooperate with state intelligence work [9]. This does not mean every device from a given country is compromised. It means jurisdictional leverage, opaque subcontracting, remote management features, and undocumented communications paths must be part of the risk model for high-consequence electronics.

Pillar two: Demand and AI exacerbate deception and verification challenges

Demand is amplifying the problem. The Semiconductor Industry Association reported that global semiconductor sales reached $791.7 billion in 2025, up 25.6% from 2024, and projected global sales near $1 trillion in 2026 [10]. McKinsey similarly notes that most assessments place the 2030 semiconductor market around $1.0 trillion to $1.1 trillion, driven heavily by AI and data centers [11].

Fast refresh cycles in AI accelerators, memory, microprocessors, networking devices, and power electronics create more reclaimed parts and more opportunities to harvest, clean, remark, repackage, and resell used components. They also shorten the time that parts remain available directly from original manufacturers. Long-life systems in defense, energy, medical, industrial control, transportation, and critical infrastructure then face obsolescence earlier and are pushed toward lifetime buys, redesigns, emulation, or open-market sourcing.

At the same time, high-consequence sectors are a small fraction of total semiconductor demand. Chip manufacturers primarily optimize roadmaps for consumer electronics, communications, automotive, cloud, data centers, and high-volume industrial markets. It is unrealistic to expect the broader semiconductor market to protect the long-tail sustainment needs of low-volume, long-life, high-consequence platforms. As authorized supply becomes harder to maintain, assurance requirements should become more risk-sensitive rather than defaulting either to blind trust or blanket testing.

AI changes both sides of the assurance equation. On the attacker side, generative tools can create realistic images, text, and multimodal content, raising risks to trust, transparency, and credibility in digital information [12]. The FBI has warned that criminals use generative AI to create fraudulent identification documents, fake credentials, synthetic images, and other artifacts used in fraud and impersonation [13]. Applied to electronics assurance, the same capability can improve counterfeit labels, generate internally consistent certificates, align lot codes with plausible manufacturing locations, and create convincing inspection records.

On the engineering side, AI-assisted design, reverse engineering, emulation, and board redesign compress development cycles. That helps legitimate sustainment teams requalify alternatives, but it also helps counterfeiters and clone manufacturers analyze, copy, modify, and scale substitute components. As design tools improve and market demand increases, cloned parts can move up the complexity curve faster than policy and test regimes evolve.

The response is not to discard documentation; documentation remains essential. The response is to treat documentation as one evidence stream among several, validate it through independent channels where possible, and pair it with physical, electrical, functional, and cyber-physical evidence when consequence justifies that added burden.

Pillar three: A zero-trust model for electronic components and modules

Zero trust in cybersecurity does not mean that nothing is ever trusted. It means no implicit trust is granted solely because of network location or ownership; access is based on explicit authentication, authorization, and context [1]. The electronics assurance analogue is straightforward: no electronic component, module, certificate, supplier claim, label, country of origin, or authorized status should be trusted solely because it appears to occupy a trusted position. Trust should be earned through evidence and maintained through monitoring.

DoD’s microelectronics assurance work provides the clearest precedent. DoD News described a shift from the trusted-foundry model to a zero-trust approach to purchasing microelectronics in which parts are validated before use [14]. OUSD(R&E) describes Trusted & Assured Microelectronics as using a quantifiable-assurance, zero-trust-based method across the microelectronics lifecycle [15]. DoD OIG evaluated the transition from trusted foundry to quantifiable assurance for custom microelectronics [16]. The common message is that trust should be measured, validated, and documented, not inherited.

For high-consequence applications, zero-trust electronics assurance has five practical principles:

• assume compromise is possible at every tier;
• verify explicitly with multiple evidence streams;
• do not place parts of uncertain provenance into safety-critical, mission-critical, or externally connected functions without compensating controls;
• preserve evidence as a data package rather than a one-time receiving note;
• and continuously update risk scoring based on anomalies, supplier performance, geopolitical changes, product-change notices, field failures, and new counterfeiting methods.

This approach does not require treating every resistor, capacitor, FPGA, memory device, microcontroller, sensor, power module, and network device identically. It requires matching the assurance burden to consequence, source risk, part criticality, cyber exposure, and substitutability. The objective is not maximum testing everywhere; it is defensible trust where failure, compromise, or latent functionality create unacceptable consequences.

Risk-tiered assurance should replace binary trust

The following tiers translate the principle into procurement posture: higher risk or weaker traceability requires stronger evidence before acceptance. Known and authorized channels remain preferred, but they should not be treated as proof by themselves. The goal is to replace blind trust with proportional assurance.

Source or channel	Baseline risk	Zero-trust assurance posture
Parts reclamation	Very High	Remaining life, prior stress, storage history, ESD exposure, and authenticity are uncertain. Use only with strong justification; require forensic inspection, electrical/environmental testing, and reliability screening.
Grey/open market	Very High	Authenticate provenance. Apply risk-based inspection and testing, including visual, x-ray, XRF, decap/die analysis, solderability, and functional/electrical verification as appropriate.
Unlicensed distributors with certificates	Very High	Treat paperwork as an artifact to verify, not proof. Confirm certificates directly with the OCM or authorized source and require independent testing for high-consequence use.
Licensed third-party/private-label manufacturing	High for critical use	Verify license scope, manufacturing site, firmware/configuration control, design authority, and sub-tier suppliers. Test against the original specification, not only form-fit claims.
OEM parts/modules from high-risk jurisdictions	High to moderate	Assess jurisdictional leverage, functionality, environmental performance, hidden communications paths, firmware update mechanisms, debug interfaces, and remote management features.
Unknown or newly approved authorized distributors	High to moderate	Qualify before use. Require direct OCM traceability, authorization-scope confirmation, logistics controls, audit rights, and sampling-based validation until performance history is established.
Known authorized distributors	Moderate	Maintain periodic authorization-scope validation, tamper-evident logistics, return and restocking controls, sample inspection, supplier monitoring, and escalation triggers for anomalies or allocation pressure.
Direct from original manufacturer (Trusted Jurisdictions)	Low to moderate	Preserve lot traceability, review PCN/ECN changes, monitor sub-tier assembly/test sites, use secure logistics, and consider lot acceptance or sample testing for critical applications.

Implementation priorities

Implementation should begin with a clear distinction between baseline evidence and risk-triggered expanded evidence. For open market purchases, the baseline should remain the established counterfeit-detection, authenticity, and test methods used for material with weak or uncertain chain of custody. For authorized-channel or direct-from-manufacturer material, the baseline is different: direct OCM or authorized-distributor traceability, confirmation that the distributor is authorized for the product and region, lot and date-code traceability, certificate review, PCN/ECN review, secure logistics, return and restocking controls, and escalation when documentation, packaging, test data, or supplier behavior is inconsistent.

Expanded technical evidence should not be automatic for all authorized material. It should be triggered by consequence and risk. Examples include programmable or connected devices, safety-critical or mission-critical use, unclear design authority, licensed or private-label manufacturing, firmware or configuration memory, remote-management capability, high-risk jurisdictional exposure, obsolescence, allocation pressure, new or unproven suppliers, or anomalies found during receiving, inspection, test, or field use.

A practical transition begins with policy language. Programs should define high-consequence electronics and require a risk score for each part or module based on source, criticality, end-use consequence, connectivity, firmware content, obsolescence status, country or jurisdiction exposure, and availability from trusted sources. Purchase orders and supplier agreements should require traceability, disclosure of sub-tier manufacturing or private-label relationships, notification of production-site changes, right to audit, secure logistics, and direct confirmation paths to the original manufacturer where available.

The second priority is technical evidence, applied according to risk rather than channel alone. Product obtained through a non-franchise distributor should continue to receive the counterfeit-detection and authenticity testing already required for that sourcing path. Zero-trust assurance does not automatically require every open market purchase to receive testing beyond that baseline. Rather, additional evidence is appropriate when the baseline test flow does not address the specific threat being considered, such as clones, undocumented functionality, firmware manipulation, configuration changes, or cyber-physical compromise.

For authorized-channel and direct-from-manufacturer product, expanded testing should also be risk-triggered rather than routine. The relevant question is not whether the part came through an authorized path, but whether the part or module is sufficiently complex, programmable, connected, safety-critical, mission-critical, obsolete, jurisdictionally exposed, or difficult to verify through documentation alone. For microcontrollers, FPGAs, memory devices, power converters, sensors, radios, network modules, and other programmable devices, assurance may need to include firmware provenance, configuration-memory review, debug-interface checks, side-channel or behavioral testing, boundary-condition testing, sample screening, and comparison to golden samples. For modules, the evidence package may include the hardware bill of materials, software or firmware bill of materials, sampled x-ray or teardown records, and verification that no undocumented radios, modems, interfaces, or remote-management paths are present.

The acquiring or integrating organization should own the risk determination because it understands the end-use consequence, system criticality, and acceptable residual risk. Suppliers, authorized distributors, manufacturers, and independent laboratories provide evidence, but they should not be expected to determine the consequence of use in the final system. In the near term, these requirements are best implemented through program requirements, purchase-order flowdowns, supplier-quality controls, customer audits, and acceptance criteria rather than through a new universal audit regime.

The third priority is organizational feedback. Every anomaly – mismatched lot history, unusual x-ray, die discrepancy, unexpected firmware, early failure, packaging inconsistency, certificate issue, supplier evasiveness, or unexplained communications capability – should feed a supplier and source-risk model. Zero trust becomes sustainable only when procurement, quality, engineering, cybersecurity, failure analysis, and program management share a common evidence base.

The fourth priority is proportionality. A low-cost passive part used in a noncritical function should not receive the same burden as a programmable device used in a safety-critical or mission-critical function. But a complex module with firmware, remote connectivity, unknown subcontracting, or unclear provenance should not be treated as low risk merely because it came with paperwork or a familiar brand name. The assurance burden should rise with consequence, complexity, exposure, and uncertainty.

Conclusion

The electronic parts assurance community is becoming more effective at managing the grey-market counterfeit problem, but the operating environment has changed. It’s no longer sufficient to base an electronic component and module assurance program on avoidance of grey market and authentication when it is unavoidable.  The modern threat includes reclaimed parts, false certificates, sophisticated clones, licensed third-party production, private-label ambiguity, cyber-physical module compromise, and state-influenced manufacturing risk. AI and accelerating semiconductor turnover make the threat faster, more scalable, and harder to detect with paperwork-based controls alone.

For high-reliability, high-consequence applications, the appropriate response is not to test every part to the same depth. The response is to replace binary trust with risk-tiered, evidence-based trust. Brand, paperwork, distributor status, and manufacturer identity remain important inputs, but they are no longer sufficient proof. The future assurance model must verify provenance, validate physical and electrical authenticity, evaluate firmware and hidden functionality, preserve chain-of-custody evidence, and continuously reassess risk. In short: trust in electronics supply chains must be earned, documented, and renewed.

Selected references

1. National Institute of Standards and Technology, SP 800-207, Zero Trust Architecture, 2020.
2. SAE International, AS6081A, Counterfeit Electrical, Electronic, and Electromechanical Parts: Avoidance, Detection, Mitigation, and Disposition – Independent Distribution, revised 2023.
3. SAE International, AS6171A, Test Methods Standard; General Requirements, Suspect/Counterfeit Electrical, Electronic, and Electromechanical Parts, 2018.
4. UK Serious Fraud Office, SFO secures 4-year prison sentence for aircraft parts fraud, February 2026.
5. U.S. Department of Justice, Leader of Massive Scheme to Traffic in Fraudulent and Counterfeit Cisco Networking Equipment Sentenced to Prison, May 2024.
6. Taipei Times, Gold Apollo denies manufacturing exploding pagers, September 2024.
7. Sky News, citing Reuters, Explosive pagers used by Hezbollah had been modified by Israel at production level, September 2024.
8. Facilities Dive, citing Reuters, Rogue communication devices found on Chinese-made power inverters, May 2025.
9. China Law Translate, PRC National Intelligence Law, Article 7 translation.
10. Semiconductor Industry Association, Global Annual Semiconductor Sales Increase 25.6% to $791.7 Billion in 2025, February 2026.
11. McKinsey & Company, Hiding in plain sight: The underestimated size of the semiconductor industry, January 2026.
12. NIST AI 100-4, Reducing Risks Posed by Synthetic Content: An Overview of Technical Approaches to Digital Content Transparency, 2024.
13. FBI Internet Crime Complaint Center, Criminals Use Generative Artificial Intelligence to Facilitate Financial Fraud, December 2024.
14. C. Todd Lopez, DoD News, DOD Adopts Zero Trust Approach to Buying Microelectronics, May 2020.
15. Office of the Under Secretary of Defense for Research and Engineering, Trusted & Assured Microelectronics program, Quantifiable Assurance zero-trust based method.
16. Department of Defense Office of Inspector General, DODIG-2022-084, Evaluation of the Department of Defense’s Transition From a Trusted Foundry Model to a Quantifiable Assurance Method for Procuring Custom Microelectronics, May 2022.
17. Defense Federal Acquisition Regulation Supplement, 252.246-7007, Contractor Counterfeit Electronic Part Detection and Avoidance System, January 2023.
18. Defense Federal Acquisition Regulation Supplement, 252.246-7008, Sources of Electronic Parts, January 2023.
19. SAE International, AS5553E, Counterfeit Electrical, Electronic, and Electromechanical Parts; Avoidance, Detection, Mitigation, and Disposition.
20. SAE International, AS6496A, Counterfeit Electronic, Electrical and Electromechanical Parts: Avoidance, Detection, Mitigation, and Disposition – Authorized Distribution.

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