Dropping the S-BOM

Mike Day • 4 October 2026

Third Party Therapy Podcast — featuring Stephen Boyer, Co-Founder and Chief Innovation Officer, BitSight. Why Static Binary Analysis Is the Missing Piece in Software Supply Chain Risk



Cyber criminals don't operate on an annual review cycle — so why do so many third party risk management (TPRM) programmes still assess supplier cyber risk that way? In this episode of Third Party Therapy, host Mike Day speaks with Stephen Boyer, co-founder and Chief Innovation Officer at BitSight, about how the cyber threat landscape has evolved, and what that means practically for anyone managing supply chain risk.

From Clumsy to Military-Grade

Stephen opens with a striking frame, referencing a recent Wall Street Journal report on how certain nation-state cyber actors have "graduated from clumsy corporate thieves to military weapons." His broader point: sophisticated, nation-state-level attacks are no longer confined to government targets. Regional airports, water utilities, oil and gas processing facilities — ordinary commercial and civic infrastructure — now sit squarely in scope, because compromising them can serve broader geopolitical or military aims.

Editorial note: the specific claim about the origin and sophistication trajectory of any named nation-state actor reflects reporting Stephen Boyer referenced on the podcast rather than an independently verified assessment, and readers should treat attribution claims in this space with appropriate caution — attribution in cyber incidents is notoriously difficult to establish with certainty.

He also points to a documented pattern from the Russia-Ukraine conflict: cyber operations frequently preceding or accompanying physical ("kinetic") military action, often disabling communications infrastructure ahead of a battlefield advantage. Separately, attacks — often disguised as ransomware but functioning as "wiperware," designed purely to disrupt rather than extract payment — have hit organisations with no direct connection to the conflict theatre at all.

Are Breach Claims Sometimes Exaggerated?

Mike raises a sharp, practical question: does the scale of data breaches claimed on the dark web sometimes get inflated for reputational effect by the attackers themselves? Stephen's answer is nuanced — he acknowledges some exaggeration does occur, particularly where an organisation has refused to pay a ransom, but points to a countervailing dynamic: attackers have a commercial incentive not to publish stolen data if the ransom is paid, since publishing anyway would undermine trust in their "business model" for future victims. He cites the Medibank breach in Australia — where sensitive medical data on millions of Australians was ultimately linked, according to police, to more than 10,000 downstream crimes — as an example of how genuinely damaging under-reported breaches can be.

Third Parties: Strengthening Security and Concentrating Risk at the Same Time

Asked whether the growing use of cloud and SaaS third parties is increasing or decreasing organisational cyber risk, Stephen's answer is "a mix of both." Consolidating infrastructure with major, well-resourced cloud providers generally raises the baseline security bar compared to organisations running their own servers and mail systems. But it also concentrates risk: a single vulnerability at a widely-used provider can simultaneously expose thousands of downstream customers, some of whom may become collateral victims without ever being directly targeted. Even Microsoft itself, he notes, has repeatedly been a direct target of major attacks — scale is not the same as immunity.

The Shift From Point-in-Time to Continuous Monitoring

The heart of the episode is Stephen's case for continuous, data-driven monitoring over the traditional annual (or less frequent) due diligence questionnaire. His figure: BitSight's data suggests a major security event — a significant vendor vulnerability disclosure — occurs roughly twice a month across the vendor landscape it monitors. An annual assessment cycle is, by definition, incapable of catching most of these in a timely way.

Editorial note: the "twice a month" frequency of major security events is Stephen Boyer's own characterisation based on BitSight's observations and has not been independently verified by this publication — treat it as one vendor's stated experience rather than an industry-wide benchmark.

He illustrates the practical value of continuous, portfolio-wide visibility with two real incidents:

• MoveIt — a file transfer tool exploited via a serious vulnerability. Stephen's team identified roughly 1,200 instances of the software across the internet — a concentrated, identifiable footprint. Crucially, several further vulnerabilities in the same product followed the initial one, meaning organisations that believed they'd already patched could still have been exposed by a later flaw, or could have been compromised before their patch was even applied.

• CrowdStrike — the widely reported outage caused by a faulty update to an endpoint protection agent running on millions of devices. BitSight used network traffic analysis (observing devices "beaconing" to CrowdStrike's update servers, then going silent) to help customers work out, within hours rather than weeks, which of their suppliers were likely affected — a question that would otherwise require contacting every third party individually.

Editorial note: the specific figure of "around 1,200 instances" of the MoveIt vulnerability is Stephen Boyer's own stated figure from the podcast and has not been independently verified here.

The Case Study: NASA and a 50% Efficiency Gain

Stephen offers NASA as a concrete illustration of scale: the organisation must conduct cybersecurity due diligence across roughly 3,000 suppliers. Working with BitSight's tooling for visibility, workflow and reporting, Stephen states NASA achieved approximately a 50% efficiency gain in that process — allowing the same team to do meaningfully more with the same resources, including supporting statutory requirements such as Section 889 vendor-restriction checks.

Editorial note: the "50% efficiency gain" figure and the "3,000 suppliers" figure are both claims made by Stephen Boyer on the podcast, presumably drawn from BitSight's own case study material, and have not been independently verified — readers should treat them as the vendor's own reported outcome rather than a confirmed, audited statistic.

Fourth Parties Hiding in Plain Sight

One of the more practically useful threads in the conversation concerns fourth party risk — specifically, infrastructure-level products that would never appear on a typical "critical fourth party" register, because they're not a named subcontractor providing an obvious critical service. MoveIt and CrowdStrike are both good examples: neither would naturally show up if you asked a third party "who are your critical subcontractors?" — yet both created genuine, fast-moving exposure. Stephen's argument is that mapping every fourth party exhaustively is neither realistic nor the point; what matters is the ability to rapidly answer "am I exposed to this?" when an infrastructure-level event breaks, using technical and open-source signals rather than relying solely on what a supplier volunteers.

Detection, Response Time, and the Limits of Prevention

Asked directly whether solutions like BitSight can prevent cyberattacks, Stephen is candid: "no one can prevent an attack." The realistic goal is reducing time to detect and respond, and shrinking the attack surface before an incident occurs — for example, identifying six specific issues during a vendor's onboarding due diligence and getting them resolved before data sharing begins, or catching malware beaconing on a system before it escalates into a full ransomware event. None of this proves a prevented attack, but it demonstrably reduces the scope and cost of the ones that do occur.

Regulation Is Starting to Have Teeth

Looking at the regulatory direction of travel — DORA in EU financial services, NIS2 more broadly across the EU — Stephen highlights Belgium's Centre for Cybersecurity (CCB) as an instructive early model: a government body directly monitoring critical national infrastructure organisations for vulnerabilities and proactively notifying them, having been among the first EU countries to transpose NIS2 into domestic law via its "Cyber Fundamental Assessments" programme. His broader observation: known, previously-disclosed vulnerabilities — not exotic zero-days — accounted for the large majority of attacks referenced in the reporting he opened the conversation with. Yet BitSight's own analysis found it takes roughly six months, on average, for half of known exploited vulnerabilities (the US CISA's "KEV" list) to be remediated across the organisations and geographies studied.

Editorial note: the "roughly six months to remediate half of known exploited vulnerabilities" figure is a claim from BitSight's own research as described by Stephen Boyer, and has not been independently verified — treat it as the vendor's reported finding rather than a confirmed external statistic.

What Makes These Programmes Succeed or Fail

Asked for lessons learned, Stephen's answer is organisational rather than technical: buying monitoring software is the easy part. Programmes fail when the capability sits in a single, isolated team with no established path to procurement, legal or the relationship managers who actually own the connection to each third party — meaning an alert about a vulnerability has nowhere productive to go. Programmes succeed when those functions are deliberately brought together (Stephen describes running workshops where stakeholders from different parts of an organisation meet each other, in some cases, for the first time) and there's a clear, cross-functional process for escalating and acting on what the monitoring surfaces.

His practical starting advice for any TPRM team considering this shift: define the specific goal and risk appetite first, start with a realistic, bounded scope rather than an all-encompassing "big bang" programme, secure an early quick win to build organisational momentum, and only then scale the approach outward.


Listen to the full episode of Third Party Therapy, produced in association with CeFPro, on Apple Podcasts, Spotify, Amazon Music, Audacy and YouTube, or visit thirdpartytherapy.com to subscribe to the mailing list.


Tags

#ThirdPartyTherapy #TPRM #CyberSecurity #CyberRiskManagement #ContinuousMonitoring #VendorRiskManagement #FourthPartyRisk #ThirdPartyRiskManagement #DORA #NIS2 #CyberDueDiligence #SupplyChainSecurity #KnownExploitedVulnerabilities #RiskManagementPodcast #HowToMonitorThirdPartyCyberRisk #WhatIsContinuousCyberMonitoring #TPRMPodcast


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A move into internal audit at Lloyds Banking Group — auditing the sourcing and property functions — turned him into a "gamekeeper," and from there he spent a decade running third party risk functions across three major financial institutions, all of which were customers of Helios's FSQS scheme, before joining Helios itself roughly 18 months ago. Ten Years of Change in TPRM Paul's account of how far the discipline has moved is stark. His first supplier management audit revealed that "due diligence" at the time amounted to a signed letter from the supplier saying "everything's fine, thank you." The regulatory framework consisted of a handful of bullet points essentially saying "you can't outsource the risk." The period from roughly 2015 to 2018 — driven by GDPR, the growth of cloud outsourcing, and European regulators waking up to the risk — triggered rapid change, followed by growing UK regulatory focus (SS2/21 and PS7/21) on operational resilience, conduct risk, and more recently ESG, which Paul says has moved from "almost at the bottom of the pile" to near the top of the risk league table. What Pooled Due Diligence Actually Is Paul's explanation is refreshingly plain: the traditional model is a "many-to-many mesh" — every buyer individually asking every one of their suppliers largely the same questions, repeatedly. Pooled or community due diligence flips this into a one-to-many model: a supplier answers a shared, standardised question set once, and that data is made available (with the supplier's consent and quality-checked) to every buyer in the community who needs it. The win is symmetric. Suppliers spend less time repeatedly answering near-identical questionnaires from dozens of buyers. Buyers get a faster start, a broader pool of pre-assessed suppliers, and — critically — a question set that reflects a decade of collective input from the buying community, not just their own risk team's best guess. As Paul puts it, being able to tell your board "this is good enough for [named peer firms], therefore we believe it's good enough for us" is valuable air cover for a new entrant to the model. From Niche to Mainstream When Lloyds Banking Group first adopted the model, it was the only buying firm in the community — making it a hard sell to suppliers. Today, Helios's UK community includes just under 70 buying firms, plus roughly 20 more across Europe, spanning tiny building societies through to major international investment banks. Paul attributes the shift to sustained pressure on TPRM budgets and headcount ("you never get, as a TPR person, someone come to you and say... would you like some more people?"), combined with a regulatory turning point around 2018-2019 when European regulation first explicitly acknowledged shared assurance as acceptable — provided the buyer using it still applies its own risk appetite to the results, rather than simply outsourcing the decision. Confidentiality and Competition Law Two objections come up repeatedly with pooled models, and Paul addresses both directly. On confidentiality, where a supplier is unwilling to upload a sensitive document (such as a full cybersecurity policy) directly, Helios instead asks granular, structured yes/no questions about the specific controls contained within that document — meaning a buyer's risk specialist can still assess control coverage without the underlying document ever being shared. On competition law, Helios never discloses which buyers work with which suppliers to other buyers in the community, never comments on individual suppliers as a collective, and never directs buyers to take action against a specific supplier — all of which would risk anti-competitive behaviour. Not a Silver Bullet — Part of an Ecosystem Paul is careful to position pooled due diligence as one part of a wider TPRM toolkit, not a replacement for the buyer's own risk judgement. Helios provides primary, source-verified data (rather than scraped or blended third-party data), but the buyer still has to decide what matters to them and act on it. His framing: "we give you the information, but your job is to decide what to do with it." Real-World Stress Testing: Russia-Ukraine One of the clearest illustrations of the model's value came with the outbreak of the Russia-Ukraine conflict. Because Helios already held country of registration, operating location and fourth party data for its supplier community, buyer firms could establish their exposure "within about half an hour" of the event breaking — rather than manually cross-referencing finance systems to work out who they'd been paying, and where. Helios then issued a bespoke follow-up questionnaire to roughly 10,000 suppliers within about ten days, with an 80% response rate — giving buyers not just a static exposure map, but live intelligence on downstream impact. The same approach was repeated for the Israel-Gaza conflict and rolling energy blackouts. Where AI Fits — and Where Helios Is Deliberately Cautious Asked about AI, Paul draws a pointed comparison to cloud computing circa 2017-2018: a lot of noise, real underlying risk, but limited clarity on exactly where the exposure sits. Helios is building a new question set specifically to assess suppliers' use of AI, aligned to the EU AI Act's risk-based, proportionate approach. But Paul is candid that Helios itself is deliberately slow to deploy AI at scale in its own data pipeline, given its core value proposition rests on primary, verified data rather than scraped or AI-generated content — and flags the emerging industry concern that large language models may increasingly be trained on data that itself originated from other AI systems, creating a quality-degradation risk over time. Editorial note: the discussion of AI training data and model quality reflects Paul Huggett's own views and industry commentary referenced on the podcast, not an independently verified technical claim. Concentration Risk and the Regulator's Blind Spot Paul also touches on Critical Third Party (CTP) regulation and the new, more detailed outsourcing and DORA registers now required by UK and EU regulators — designed to help regulators identify concentration risk across the financial sector. He's candid that Helios, precisely because of the same competition and confidentiality constraints discussed earlier, cannot fill this gap entirely: it knows what a supplier does, but not what each buyer considers critical about that relationship, since criticality varies hugely between an insurer, a reinsurer, a building society and an investment manager. The Direction of Travel: From Data to Assurance Looking ahead, Paul sees the community model extending from data-gathering into genuine assurance — Helios has already introduced ESG benchmarking that lets suppliers see how they compare to peers, and has launched pooled, supplier-funded virtual site visits testing controls across the top operational risk domains. Notably, he observes that resistance to pooled assurance has historically come more from buyers wanting to "do things their way" than from suppliers, who are generally keen to spend less time on duplicate assurance requests. A Practical Starting Point For any organisation considering this path, Paul's advice is to look at your own organisation from the supplier's point of view: how many different, overlapping data requests are you sending out? Are you actually using everything you collect, or gathering data you never act on? And do you genuinely understand your broader (not just your most critical) supplier population — because, as Paul notes pointedly, "Covid did not care that it was taking out your workforce from a whole swathe of your medium risk suppliers." His clearest warning, drawn from watching organisations invest heavily in shiny new source-to-pay platforms: the technology is rarely the problem. "Systems and technology are not going to solve your problems. They're just going to give you a shinier problem to grapple with," unless matched with the cultural change and data discipline to actually populate and use them. Listen to the full episode of Third Party Therapy, produced in association with CeFPro, on Apple Podcasts, Spotify, Amazon Music, Audacy and YouTube, or visit thirdpartytherapy.com to subscribe to the mailing list. 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