2026 Evidence Edition — Vulnerabilities as Wasting Options on Access
This is a ground-up rewrite. Earlier editions (2022, 2022-revised, 2022-revised-v2) layered insights additively across 23 parts. This edition reorganises around emergent themes, integrates Mark Dowd's 2022, 2023, and 2026 analyses as one continuous body of work, and treats every forward-leaning claim as a falsifiable proposition that gets a steelman and an external counter.
Drawing on Mark Dowd's OffensiveCon 2022 keynote, BlueHat 2023, Risky Business HF13, and a 2026 podcast interview on the zero-day exploit marketplace. Casey Ellis — April 24, 2026.
The thesis in one sentence: A vulnerability has no intrinsic price; its value is the expected payoff from converting a defect into durable access for a specific buyer, minus discovery, chaining, maintenance, exposure, and time-decay costs — and AI is now compressing the time axis on both sides of that equation.
Seven actor models pay different prices for the same technical artifact: (A) the boutique top-tier offensive customer with a maintenance contract; (B) state-directed volume collection with high tolerance for low-cost, low-maintenance bugs against unpatched targets; (C) initial-access brokers selling validated paths to outcomes, not bugs; (D) ransomware operators running an ROI calculation against substitute access vectors; (E) chaotic and ideological actors who price-clear for reasons the formula cannot capture; (F) commercial surveillance vendors amortising one chain across many customers; and (G) defensive intelligence buyers (ZDI, broker-funded vendor programs) pricing bugs against the cost of a class kill rather than the cost of an exploit.
AI is doing two things simultaneously. On the offensive side it is collapsing the floor — commodity-tier discovery is becoming cheap enough that less-sophisticated vendors face a wave of zero-days they cannot patch fast enough. On the defensive side it is collapsing the cost of class kills and re-architecture — vendors who previously needed two years to ship a memory-safety transition are doing it in months. The two effects compound to compress the expected useful life of a non-provable exploit. At T1, however, the expert tier is widening its lead, not closing it: the AIxCC podium was filled by elite human teams that built the AI, not by AI alone. And the AI competition itself is geopolitical — DeepSeek's V3 / R1 release in December 2024 and January 2025 demonstrated that frontier reasoning capability is no longer a Western monopoly, while NIST's CAISI evaluation found DeepSeek agents roughly 12x more likely than US frontier models to be hijacked for malicious instruction-following. Western AI vendors carry a guardrail tax their Chinese counterparts do not pay.
Every theme above lands inside a US-China structural rivalry that is now the dominant exogenous variable. The PRC has built (per the Atlantic Council's Crash, exploit, and burn) a comprehensive feeder system from CTFs to MSS/MPS/PLA that the West has no equivalent of. China's RMSV regulation routes vulnerability discoveries to MIIT within 48 hours. The 2024 i-Soon leak revealed pricing ($10K-$75K per compromised email account; ~$55K to compromise a foreign ministry) inside a contractor relationship with 43 separate provincial and municipal security bureaus. The 2024 Volt Typhoon advisory documented PRC actors pre-positioning in US critical infrastructure for "five years or more"; the 2025 Salt Typhoon advisory documented compromise of nine US telcos and the lawful-intercept systems used to service CALEA wiretap requests. US Treasury sanctioned three Chinese cyber contractors between December 2024 and January 2025; the Department of Justice indicted twelve i-Soon and APT27 actors in March 2025. The Pall Mall Process produced a Code of Practice for States in April 2025 that twenty-three governments have signed and that China has not engaged with. Whatever the marketplace looks like in the abstract, this is the gravitational field it is moving inside.
Observable: public bounty ceilings, vendor mitigation rollouts, KEV catalogue growth, M-Trends and DBIR exploitation timelines, MIE on A19 silicon, Big Sleep CVE-2025-6965. Reported: Crowdfense and Operation Zero asking prices, Cellebrite revenue growth, Paragon proliferation. Inferred: government direct pricing, the structure of Five-Eyes procurement, exploit-stockpile depletion rates. Speculative: the AI-vs-defender equilibrium past 2028, HarmonyOS reaching parity with iOS, the persistence of effect-based buying once cloud providers harden their telemetry surfaces.
The cost-curve thesis depends on whether AI's defender tailwind generalises beyond mobile and browser to enterprise edge devices — and the 2025 GTIG data suggests it does not. The bifurcation thesis depends on whether the mid-tier truly thins; if the Intellexa / Cytrox layer survives, the picture stays trifurcated. The effect-based buying thesis is bounded at the top — Crowdfense's 2024 expansion to a $30M acquisition program with $9M zero-click bounties is direct evidence that the premium tier still pays for capability, not effect. These are not fatal counterarguments; they are the boundary conditions of the argument.
Most arguments about exploit value are arguments about different things. The pricing object — the thing the buyer pays for — is rarely the bug. Four distinct objects circulate through the market, and most published prices conflate them.
| Object | What it is | Who pays for it |
|---|---|---|
| Defect | The latent flaw. A condition in code or hardware that violates an invariant. Most defects are never weaponised. | Bug bounty programs and academic researchers. Apple Bug Bounty pays observable maxima; the published 2025 program update raised full-chain payouts to $2M. |
| Exploit primitive | A validated way to turn the defect into a useful capability — a write-what-where, a type confusion, a sandbox-relative read. | Brokers and chain assemblers buy primitives as Lego pieces. Component-level prices are rarely public. |
| Chain | A composed end-to-end capability that reaches an objective — messaging-app entry to persistent kernel implant, or browser to root. | Government direct buyers and commercial surveillance vendors. Crowdfense's 2024 program publicly listed $7M iOS, $5M Android, $9M zero-click SMS/MMS for full chains. |
| Access | The operational product the downstream buyer ultimately wants — a target's location, communications, photos, or session tokens. | End customers (intelligence agencies, surveillance services, even corporate buyers via investigators). Most do not buy chains; they buy outcomes. |
Once the four objects are separated, several long-running disputes resolve. Bounty payouts and broker prices are not "the price of an iOS bug"; they are prices on different objects with different liquidity, exclusivity, and buyer obligations. A Five-Eyes contract is not paying for a chain — it is paying for maintained access through the chain's degradation curve. A ransomware affiliate is not buying a defect — they are buying access, and they will pay for stolen credentials, an n-day, or a 0-day with equal indifference if the operational outcome converges.
The great-power frame sharpens the taxonomy. The March 2025 DOJ indictment of i-Soon documents pricing on a different pricing object than Western broker price sheets: $10,000 to $75,000 per compromised email account. That is access pricing, and it is what the PRC end customer was actually paying for — not chains, not exploits, not defects. The 2024 i-Soon leak put a comparable line item on the wire: roughly $55,000 to compromise the Vietnamese Ministry of the Economy. When the same firm priced individual MPS contracts in the low- to mid-six-figures and brokered "tens of millions" in revenue from MSS and MPS bureaus, the underlying object was always operational outcome, never bug. Western analyses that treat the Chinese market as an opaque mirror of the Western broker tier miss that the pricing object itself is different.
A second conflation runs orthogonal to the pricing object: the gap between an advertised offer and a realised sale. Two ex-brokers have now put first-hand numbers on the intermediary's cut. Maor Shwartz, who founded the brokerage Q-recon, disclosed his firm's fee schedule on stage at Black Hat 2019 — 17% from companies, 15% from governments — paid with no advance: a percentage on validation (a ~14-day window), the remainder split over three to six months, deals under $100K settled only after the exploit checks out. "The grugq," the independent middleman behind the canonical 2012 Forbes price chart, reported the same ~15% commission — and that roughly 80% of his revenue came from US buyers "because they pay more." That ~15–17% wedge, stacked on the offer-vs-sale discount the Williams case exposes (an advertised $20M ceiling against a $162K-per-exploit clearing price), is why a broker's published sheet is a bounding curve, never a transaction record.
This is the foundation. Every later section is about which object is priced, by whom, against what alternatives, and over what time horizon.
Five forces shape what a buyer will pay for any of the four pricing objects above. They are not weights in a tidy multiplicative formula — they interact, dominate one another at different points in the bug lifecycle, and respond to second-order pressure from substitutes. They are the language of valuation.
This is the insight Mark Dowd has been hammering since OffensiveCon 2022, and it remains the most under-priced variable in public discussion of the marketplace.
"People dramatically underestimate maintenance cost. You find a bug, you write an exploit, and now you're on a treadmill. Every patch Tuesday, every point release, you're checking: did they break it? Did they change the heap layout? Did they add a mitigation? That cost is ongoing and it compounds."
Total cost of ownership for an offensive capability is discovery plus development plus ongoing maintenance. Most external valuations count only the first two. On hardened T1 targets the third dominates the first two combined within 12-18 months of the chain reaching production. This is why "asking price" headlines mislead: a $7M chain that requires $200K/month of maintenance has an entirely different unit economics than a $7M chain that needs occasional touch-ups.
Vulnerabilities are wasting options. Their value decays as exposure, patching, and detection close in. The decay curve is not smooth. It is shaped by the patch cadence of the target (monthly for Android, a few weeks for Chrome's stable channel, irregular for many enterprise products) and by the appearance of competing capabilities. The 2025 RAND data — still the cleanest empirical work on stockpile dynamics — found median latent life around 6.9 years with a collision rate of 5.7% per year, but those numbers are from a 2017 dataset and almost certainly overstate residual lifetime in 2026 conditions.
Time decay under great-power pressure: Recorded Future and SentinelOne LABScon analyses found that CNNVD beats NVD to publication 43% of the time on average — but only 3% of the time when a vulnerability is being actively exploited by Chinese APT groups, and CNNVD has retroactively altered 267 publication dates to obscure the MSS evaluation window. The decay curve in China is artificially extended by deliberate disclosure-timing manipulation.
The directional shift: while China's adversarial mirror is operating at full capacity, the US side of the same infrastructure has been hollowing out. On February 13, 2024 NIST publicly acknowledged a "growing backlog" of unanalyzed CVEs in the National Vulnerability Database and announced it would stop fully enriching incoming submissions, citing resource constraints. By mid-2024 the backlog was widely reported in the tens of thousands. CISA stood up the Vulnrichment ADP container in May 2024 to fill the gap, and in April 2025 had to scramble to extend MITRE's CVE Program funding after a contract lapse threatened the entire CVE numbering authority. The asymmetry is the load-bearing point: at the same moment the PRC's CNNVD continues to operate as a state-controlled vulnerability funnel that grants MSS first refusal on disclosed bugs, the US-led centralized infrastructure has been partially decommissioned, federated across CISA / MITRE / private CNAs, and forced into emergency funding mode. Western analyses that assume symmetric decay across actors mis-price the Chinese capability lifecycle — and the Western system that historically anchored the comparison is no longer reliably doing so.
"The detection environment has fundamentally changed. It's not just about whether your exploit works — it's about whether using it gets you caught. Attribution capability is a tax on every operation, and it increases the effective cost of deployment."
A burned exploit is not just worthless — it is negative-value. It exposes attribution chains, leaks technique, retires similar capabilities by signature, and creates diplomatic friction. Dowd's 2026 update reinforced this with a sharp methodological point: vendor "Lockdown Mode prevented X attacks" claims are silly because operators select capability against observed defenses; if a target runs Lockdown Mode the operator deploys something else, not the same payload.
"If you look at something caught in the wild and say 'if they were doing this then it wouldn't have worked' — what you're leaving out is they deployed exactly what they needed against that target to succeed. They would have deployed something else. So it's a bit disingenuous to make that claim."
The 0-day is rarely the only path to the operational effect. The substitution set includes n-days, stolen credentials, supply chain compromise, insider recruitment, telecom interception, cloud-account takeover, and increasingly social engineering at scale. Mandiant's M-Trends 2025 found stolen credentials had moved up to the second-most-common initial access vector at 16% of investigations, behind only exploits at 33%. Verizon's 2025 DBIR reported 22% of breaches across 12,195 incidents involved credential abuse. The exploit-or-nothing framing is a category error; rational buyers price chains against the cheapest substitute.
Conversion is the gap between holding a defect and producing the operational outcome. It encompasses chain assembly, OPSEC, deployment infrastructure, target reconnaissance, and the human operator's tradecraft. Two buyers holding the same defect may extract radically different value because their conversion machinery differs by orders of magnitude. This is why state-direct prices look high in the abstract and reasonable in context: the price is paying for a capability that ships into a conversion pipeline costing tens of millions to maintain.
Burn discipline differs by regime. The Atlantic Council's DeSombre Bernsen documents that "truly burning a capability is much rarer in China." The PRC system runs an "A-team to D-team cascade": elite teams use a vulnerability first, and the same exploit is then handed down to subsequent tiers of operators, often after the initial use is detected. The Microsoft Exchange 2021 case is the canonical example — one Chinese APT group exploited the vulnerability two days before disclosure to Microsoft; multiple other Chinese groups began exploiting it en masse within twenty-four hours of the public patch. In Western procurement, "burning" a capability is a discrete, costly event that operators avoid by selecting capability against observed defenses. In the Chinese model, the burn is amortised across many operators. The economics are not comparable.
Seven actor models pay different prices for the same technical artifact. They differ on what object they buy, how they price substitutes, what maintenance they tolerate, and what obligations they impose. The taxonomy is not exhaustive — it is the minimum disambiguation needed before any "what is the price" question makes sense.
| Model | Object purchased | Pricing logic | Maintenance tolerance |
|---|---|---|---|
| A. Boutique Top-Tier Offensive (NSO-style) | Full chain plus maintenance contract | Cost-plus for exquisite chains; high obligations and exclusivity | Very high — engineers maintain chains as a service |
| B. State-Directed Volume Collection (PRC-style) | Many chains and access points; tolerant of brittle bugs against unpatched targets. i-Soon priced inboxes at $10K-$75K against ~43 separate provincial and municipal security bureaus. | Aggregate access value rather than per-chain ROI; decentralized procurement down to municipal PSBs (per DeSombre Bernsen) | Low — rotates through unpatched targets faster than maintenance compounds; A-team to D-team cascade extends asset shelf-life |
| C. Initial Access Brokers | Validated access — not bugs | Per-foothold pricing; n-days and credentials beat 0-days when both work | None — access is sold, not maintained |
| D. Ransomware Industrial | Access + tooling for encryption + leverage | Expected ROI net of negotiation, dwell-time risk, and substitute access vectors | Moderate — ephemeral implants preferred |
| E. Chaotic / Anti-Economic | Whatever is available; ideological or expressive | Outside rational pricing — the formula breaks here | Variable |
| F. Commercial Surveillance Vendors | One full chain amortised across many sovereign customers | Recurring SaaS-style licensing on top of chain investment | Very high — chain longevity is the asset's value |
| G. Defensive Intelligence Buyers (ZDI, broker-funded VRPs) | The defect, plus the option to disclose it | Cost-of-class-kill, not cost-of-exploit | None — bugs are returned to vendors |
Two structural notes from the 2026 Dowd interview tighten this taxonomy. First, the top-tier offensive market is gated by trust networks, not procurement — a fact that materially affects how policy proposals around "lawful hacking" should be modelled.
"For most of the existence of my previous company prior to acquisition we didn't do any real sales — we very rarely got introduced to new customers and we only took word-of-mouth introductions from our existing customers that we trusted. Even within the Five Eyes, we didn't just go 'hey if you're in the Five Eyes you're in.' We had to be convinced that their OPSEC and the framework under which they operated was something we could agree with."
Second, the market boundary is wider than "exploit pricing." Effect-based buyers may route demand into cloud abuse, telecom interception, or sister-company services that produce the same operational outcome.
"There's a lot of commercial entities — there's a market for producing an effect, and the way they produce that might be very different than going for just endpoint exploitation."
AI is the largest live variable in vulnerability economics. It changes the time axis on both sides simultaneously. Three forward-leaning claims dominate the discourse; each gets a steelman and a counter.
Net read: directionally true on discovery, weak on deployment. The vendor that finds the bug five days earlier still has to ship the patch through a six-week downstream pipeline.
Net read: strong at the iOS / Pixel / kernel tier; softening at the privesc tier. The expert advantage widens at the very top, narrows in the middle.
Dowd's framing of why the asymmetry holds is worth quoting at length:
"People who have a very in-depth technical knowledge of certain platforms or code bases have an advantage with AI acting more as a force multiplier for them than [for] someone else. They have already a good intuition of exactly where to look and the right questions to ask the LLM. If you have an LLM hypothesize about vulnerabilities in a particular code base, all of it sounds pretty plausible — and an experienced person can go: I know that's not a thing. Let's spend our time on this."
Net read: partially supported, narrowly. The defender tailwind is real for hyperscale managed-stack vendors (Apple, Google first-party, Microsoft kernel). It does not reach enterprise edge appliances, and it does not apply at all to the federated FOSS supply chain — see the qualifier below.
FOSS supply-chain qualifier: the C5 thesis assumes a vendor architecture where a merged pull request becomes a shipped patch within a release cycle the vendor controls. Most of the world's exploitable code does not live in that architecture. Open-source dependencies travel through maintainer review (often a single unpaid individual), upstream release, distro repackaging, container-image rebuild, transitive-dependency resolution, and downstream consumer adoption — a chain measured in months to years rather than weeks. AI does not compress that chain; if anything, it pulls it the wrong direction by lowering the cost of malicious or low-quality contributions to under-resourced projects. Three live cases anchor the asymmetry:
xz-utils (CVE-2024-3094, March 2024). "Jia Tan" spent roughly three years building maintainer trust on a critical compression library before merging a backdoor into builds destined for systemd-linked SSH; the CISA advisory documents the social-engineering pressure campaign on the original maintainer Lasse Collin, who was openly burned out and looking for a co-maintainer. Andres Freund caught the backdoor accidentally via a SSH-handshake performance regression. Russ Cox's forensic timeline traces the operation. Log4Shell (CVE-2021-44228, December 2021). Sonatype's 2024 State of the Software Supply Chain reports that years after disclosure, vulnerable Log4j versions are still downloaded approximately one in eight times the package is requested. AI does not fix the millions of unmaintained applications still pulling them. Polyfill.io (June 2024). A domain-takeover after the original maintainer sold the domain to a Chinese-registered entity; the SanSec analysis documents over 100,000 sites compromised, including Hulu and JSTOR. The patch was "stop using polyfill.io," but downstream removal took weeks for sophisticated buyers and is still incomplete elsewhere.
The structural point: the FOSS supply chain is the exact inverse of the managed-vendor ecosystem the C5 thesis describes. Authority is decentralized, maintainer capacity is the binding constraint, downstream propagation is unowned, and trust is built socially rather than contractually. The Linux Foundation's Census III documents that a small number of critical packages have one or zero active maintainers. AI raises the floor for attackers in this ecosystem (cheap PRs, cheap social engineering, cheap fuzzing of obscure dependencies) without raising it commensurately for defenders, because there is no vendor budget to spend the AI tailwind on. Great-power competition compounds the problem: PRC-affiliated maintainer pressure (the Linux kernel "hypocrite commits" controversies, Huawei contribution patterns) and Russia-aligned maintainer departures (the 2024 Linux kernel patch removing Russian-affiliated maintainers) are now structural risks. The defender tailwind is real where it lands; the FOSS supply chain is exactly the segment where it does not.
"The vendors have access to the same technology and in general dramatically more compute, not to mention potentially exclusive access to [vendor-side AI tooling]. They have the ability to find the vulnerabilities that other people are finding at scale and to improve the throughput of their patching. As the cost of development goes towards zero, it's not that difficult for them to re-architect significant blocks of not just the vulnerable code but their patching infrastructure. Things that before were a two-year effort — they can iterate quickly on now."
The AI inflection is also producing a second-order externality that does not show up in price data: vendor guardrail policy is becoming a chilling effect on defenders, not just researchers. Dowd's framing is sharp on this:
"Anybody who's in the defensive space right now is so beholden to these companies that they might get left out, not get involved in the cyber-whatever program, they might not get access to this or that thing — what you're getting is just no real discussion or criticism around how these guardrails are being proposed and whether they're being properly rolled out and if it's being given access to the right folks. It's more about a chilling effect than a discussion of 'hey, this is a tool.'"
The market-power asymmetry between frontier AI vendors and security practitioners is shaping what counts as "responsible" before the empirical question of marginal harm has been settled. This is a missing externality in any "AI is net-defensive" model.
The defender-tailwind framing rests on a Western-centric reading of who has the AI. China's offensive cyber program is already deeply integrated with AI institutions and runs without the guardrail tax. Three concrete observables anchor this:
Huawei's HULK Robot. Margin Research's Watching the Watchers analysis found Huawei's automated bug-finding system was credited with around 25% of the bugs fixed in Linux 5.4 and 15% of the bugs fixed in Linux 5.10, contributing roughly 1,689 patches in their 2021 dataset — about three times the volume of the open-source Syzbot. Margin's structural concern is that Huawei tests fixes on its openEuler distribution before upstreaming, opening a window in which the bug is known to the Chinese ecosystem but not yet patched in mainline Linux.
DeepSeek as Chinese cyber capacity input. CSIS and Reuters reporting documented DeepSeek's V3 (December 2024) and R1 (January 2025) reaching near-frontier reasoning performance on nominally export-compliant H800 silicon, with a senior US State Department official confirming DeepSeek's references in 150+ PLA procurement records. NIST CAISI's September 2025 evaluation found DeepSeek agents roughly twelve times more likely than US frontier models to be hijacked into malicious instruction-following — phishing, malware execution, credential exfiltration. Cisco's red-team evaluation found DeepSeek failed to block any harmful prompt in their representative set, where GPT-4o blocked 86%.
Civil-military fusion AI labs. CSET's Academics, AI, and APTs identified six Chinese universities (including Harbin Institute of Technology, Shanghai Jiao Tong, BUPT, and Sichuan University) running AI labs that have direct relationships with state-aligned APT groups. Under the 2017 Civil-Military Fusion framework and the 2017 National Intelligence Law (Article 7's universal duty to support intelligence work), commercial AI tooling flows into state cyber programs without the contractual ceremony Western firms require.
The asymmetry is the operative point. The Western defender-tailwind argument assumes vendors will use AI to ship class kills faster than offensive operators can find new chains. The China-side picture is that offensive operators have access to AI tools that ship without guardrails, run on Chinese hardware that Western export controls have failed to fully constrain, and feed a state pipeline that imposes mandatory disclosure within forty-eight hours. The defender tailwind exists in the West; the offensive tailwind exists everywhere else. Whether the former wins on net depends on which side's tailwind is structurally larger — and that is now an open question rather than an obvious one.
Dowd's 2022 keynote argued that for hardened tier-1 targets the cost curve was approaching an inflection: it was becoming more expensive to attack than to defend. Three years later that thesis is testable against shipping evidence. The deeper question, however, is the mechanism: why does the curve cross? The answer is not just that mitigations get cheaper. It is that the rate at which different actors independently find the same bug is rising — and rediscovery rates are the load-bearing variable behind every other claim in this paper.
Trey Herr, Bruce Schneier, and Christopher Morris's "Taking Stock: Estimating Vulnerability Rediscovery" (Belfer Center, 2017, revised October 2017) is the foundational empirical work on this question, and its findings reshape every economic model that depends on bugs being privately retained. Herr et al. analyzed disclosure records across Chrome, Firefox, Android, and OpenSSL and found an aggregate annualized rediscovery rate of 12.7%, ranging from 10.8% for Chrome (2009-2017) to 21.9% for Android (2016-2017), with revised Firefox at 14%. For Chrome and Android, more than 60% of all rediscovery occurred within a single year. OpenSSL was an outlier at 3.4%, but on a small sample (57 bugs, 2 duplicates) the authors flagged as low-N.
The Herr findings sit in direct tension with RAND's 2017 Zero Days, Thousands of Nights, which estimated annualized rediscovery at 5.76% and under-90-day rediscovery at less than 1%. The two papers measured different populations — RAND used a small private dataset of held zero-days, Herr used public disclosure records as a proxy for discovery — but the gap is wide enough to matter. Earlier work by Ozment (2005) found 9% rediscovery on immature software; Finifter, Akhawe, and Wagner (2013) found 4.6% for Chrome alone. The policy consequence has always been the Vulnerabilities Equities Process: if rediscovery is closer to 1%, retention dominates; if closer to 22%, disclosure dominates.
For an economics paper rather than a policy paper, the consequence is more structural. Rediscovery is the rate at which any privately-held capability faces the risk of becoming worthless — not because it was burned in operation, not because it was patched in the normal cycle, but because someone else independently found it. Every other variable in this paper interacts with that rate:
Net read: the headline rate is moving up; the elite-chain population is the unmeasured tail. The directional claim is robust; the magnitude for any specific market segment is not yet pin-down-able.
The equities-process implication: the United States Vulnerabilities Equities Process was designed in the era when 5.76% rediscovery was a defensible upper bound. The Herr / Schneier / Morris work in 2017 made retention harder to justify on cost-of-collision grounds. The 2024-2026 AI-assisted discovery wave makes it harder still. China's RMSV regulation (§9) is the inverse: a state-mandated funnel that captures rediscovery from domestic researchers and routes it to MSS first. The two equities regimes are diverging at exactly the moment the empirical case for retention is weakening on the Western side.
Net read: directionally supported but contested. Costs are up, but demand is paying for the increase rather than retreating to substitutes — at least at the top of the market.
Great-power qualifier: the cost curve crosses cleanly only for hardened-mobile and browser surfaces where the West has spent the engineering capital. It has not crossed for enterprise edge devices, telecom infrastructure, or critical-infrastructure OT. Salt Typhoon and Volt Typhoon (Section 6) both exploited the segments where Western vendors have not invested at the same rate as Apple and Google. The cost curve is geographically and sectorally uneven, and PRC operators are picking exactly the seams where Western mitigation engineering has not landed.
"We're approaching an inflection point where, for hardened targets, it's getting harder to hack than to secure. The cost curve is crossing. That doesn't mean bugs stop existing — it means the economics flip. Finding becomes more expensive, maintaining becomes more expensive, and the buyer needs to pay for all of it."
Net read: the steady-state effect is real, but year-one bypass headlines are not the same evidence as year-five durability. Dowd's 2026 update is the right framing for this.
"Most mitigations are deployed somewhat conservatively because they run the risk of destroying the user experience. A new mitigation will come out, they'll deploy it but relatively conservatively — turned down fairly low. A bunch of people come out and say 'man it's so easy to bypass this.' Over time it gets more improvement, and then the noise about how you can just bypass that mitigation starts dying down."
Net read: compression is real for top-of-stack edge devices; the broader CVE population is more bimodal — either weaponised within days or never.
Effect-based buying is the most under-priced shift in the 2026 marketplace. The framing comes directly from Dowd:
"The consumers of these products from a certain standpoint don't actually care about exploits, and they also don't care about the complexity of them. They're trying to achieve an effect. If a shell script did it, that would be great — we'll pay for it. So they start looking at: how do we achieve what we need to achieve? Can we live with less? Do we need a full team?"
Net read: true for the broad market; bounded at the top tier. The effect-based substitution thesis explains the broad middle and the commodity floor. The capability-based premium is intact for sovereign customers buying exquisite chains.
Persistence used to be table stakes in offensive operations. In Dowd's 2026 framing, it has been quietly demoted from feature to optional liability:
"Persistence is obviously a very useful capability for a customer to have in their arsenal, but whether they deploy it or not depends on various factors. The complexity of finding a useful persistence bug and using it is also a fairly large investment in effort, and most people, I would say, it's not really critical in a lot of cases to have persistence anyway. As things get more difficult you spend more and more of your engineering effort on maintaining the critical portions of the chain."
Net read: reframe needed. Endpoint persistence is optional for memory-resident operators. Edge persistence is now central. The economics differ by network position, not by era.
Reboot-as-defense follows from this directly. Dowd was sharp on the Triangulation case: phones reinfected every two-three days produced "a lot of opportunities for artifacts, for capturing network traffic, for doing man-in-the-middle, catching the full exploit chain." Each redeployment is a capture opportunity — an externality that scales with the target's reboot frequency.
The logical conclusion of effect-based buying is that as endpoint chains get longer and more brittle, the cloud account, the telco, and the human asset become the cheaper substitute. Dowd traces the pattern explicitly:
"If the effect that you wanted was to get location and emails and messages — these are all sitting on the cloud in a backup somewhere — why am I bothering with the endpoint at all? There's a lot of commercial entities — there's a market for producing an effect, and the way they produce that might be very different than going for just endpoint exploitation."
For an economics paper this is the third axis of substitution. The first is 0-day vs. n-day (time). The second is exploit vs. credentials (vector). The third is endpoint vs. cloud-or-telco (architecture). All three operate simultaneously and interact: when MIE pushes endpoint chain prices into the eight figures, cloud account takeover at $5K from an access broker becomes the rational substitute for many operational objectives.
The 2024-2025 Salt Typhoon campaign is the cleanest illustration of effect-based substitution at nation-state scale. The August 2025 CISA / NSA / FBI joint advisory, co-signed by twelve partner nations, attributed compromise of nine US telecommunications carriers (Verizon, AT&T, T-Mobile, Lumen, Charter / Spectrum, Consolidated Communications, Windstream, and two unnamed) to PRC state-sponsored actors. Senator Mark Warner (Senate Intelligence Committee Vice Chair) called it the worst telecom hack in US history. The PRC actors stole bulk call detail records on more than a million subscribers concentrated in the Washington DC metro, intercepted live calls and SMS of fewer than one hundred highly targeted individuals (including reportedly the Trump and Vance campaign principals), and — most strategically — accessed the systems used to service US lawful-intercept (CALEA) wiretap requests.
The operational outcome — access to a target's location, communications, and metadata — was achieved without endpoint exploit chains. The PRC operator substituted upstream telecom infrastructure compromise for downstream device compromise. US Treasury sanctioned Sichuan Juxinhe Network Technology in January 2025 for direct involvement in Salt Typhoon. The economics implication is that effect-based buying at the top of the market does not necessarily route through the broker market for chain-level capability — it can route through a contractor relationship that buys carrier infrastructure access. The substitution thesis is strongest at the volume-collection tier exactly when it is bounded at the boutique-chain tier (Section 7).
The companion campaign, Volt Typhoon, illustrates the substitution principle from another direction. The February 2024 CISA advisory documented PRC actors maintaining access in some US critical-infrastructure environments "for at least five years" using living-off-the-land tradecraft (wmic, ntdsutil, netsh, PowerShell) rather than custom malware. FBI Director Wray testified to the House Select Committee on the CCP in January 2024 that PRC hackers were pre-positioning to "wreak havoc" on US infrastructure and that PRC cyber personnel outnumber FBI cyber personnel by at least 50 to 1. Volt Typhoon substituted credential reuse and edge-device compromise for chain-based capability against hardened mobile targets — and the operational effect (latent disruption capability against energy, water, communications, and transportation) is, by every conventional metric, more strategically valuable than any ten iOS chains.
The exploit market is splitting along a clear seam. A premium-few tier sells exquisite full chains to sovereign customers at multi-million-dollar price points with maintenance contracts and exclusivity. A commodity-many tier sells "button" tooling to many less-technically-sophisticated customers cheaply. The middle is thinning.
The pattern is documented across multiple authoritative sources:
Net read: the best-supported claim in this paper. Bifurcation is observable and trending, with no authoritative source contesting it.
Dowd's framing of how this happened is mechanically clean. As mitigations stack and chains get longer, brittler, and more expensive, the producer faces a choice: serve a few customers paying top dollar, or commoditise and serve many customers cheaply.
"Grayshift went the opposite direction — they're going to sell it to a lower technically capable tier of customer, and it's going to be like a button, and it will actually be quite cheap. Try and go for tons of customers instead of a few customers paying top dollar. So the economics change as things get more difficult — you can sort of do one or two of these models."
Net read: strongly supported for hardened T1 zero-click; weaker for commodity 1-click. The Zerodium counter predates 2024 and applies to a different market tier — the cleanest evidence available, and explicitly the weakest counter in this paper.
The paradox resolves by decomposing chain cost. Discovery cost is collapsing — AI helps. Weaponisation cost is exploding — modern chains require five or more components where three sufficed five years ago, each independently maintained. Maintenance cost compounds with each component. The dominant cost has shifted from "find a bug" to "compose and maintain a full chain," and the latter is moving in the wrong direction for the buyer.
The mobile platform threat model is fragmenting along geopolitical lines. The 2010s assumption that iOS-and-Android encompasses the strategic surface no longer holds in Asia, and the regulatory regimes around vulnerability disclosure are themselves diverging.
Net read: in-China balkanization is real and well-documented. Global platform fragmentation is bounded by HarmonyOS's adoption ceiling outside China.
"[Huawei] went from a joke of a vendor to being really quite good in many respects. Going microkernel instead of just doing Linux again is quite a move. They've got quite a lot of money, and they're heavily incentivized to make it really secure — anyone that has a platform that's de facto a national asset is obviously going to be a prime target for political adversaries."
National-asset status creates a funding gradient that pulls security investment toward parity with Apple and Google. Western analyses that assume non-Western platforms are fish-in-a-barrel are using a 2018 mental model. The economic implication is a third axis on the cost curve: vendor sophistication is no longer a Western monopoly, and the comparative advantage in mitigation engineering may not last the decade.
HarmonyOS adoption update. Per Counterpoint and SCMP reporting, in Q2 2025 HarmonyOS reached 17% of the China smartphone market and iOS 16% — the sixth consecutive quarter HarmonyOS has surpassed iOS domestically. Caixin reports the developer base hit eight million by mid-2025. HarmonyOS NEXT, the first fully Android-incompatible build, shipped on the Mate 70 series in late 2024; Huawei committed all 2025 flagship devices to NEXT. The 2021 China-Russia joint communiqué committed both nations to coordinated development of HarmonyOS, openEuler, and Russia's Aurora OS as a counter to "the US monopoly." The threat-model bifurcation that started as a regulatory choice in 2021 is now a platform reality with eight-figure user counts.
The competition pipeline. Per the Atlantic Council's Capture the (Red) Flag, China runs fifty-four annually-recurring hacking competitions that route vulnerabilities into MSS, MPS, and PLA branches. The inaugural Matrix Cup in June 2024 offered ¥18M (roughly $2.5M) for zero-day exploits; it was co-organized by Integrity Tech, the firm Treasury sanctioned in January 2025 for its role in Flax Typhoon. Tianfu Cup returned in January 2026 under MPS organizational lead with an explicit AI-assisted vulnerability-discovery track and the contest website blocked to non-China IP addresses after the event. The closed-format consolidation continues.
Section 7 established that the Western exploit market is bifurcating — premium-few primes at the top, commodity-many products at the bottom, the middle thinning. Section 8 established that the regulatory environment in China is structurally different from the West. The Atlantic Council's June 2025 report Crash, exploit, and burn: Securing the offensive cyber supply chain to counter China in cyberspace by Winnona DeSombre Bernsen is the first comparative study of the two acquisition models — and it gives the bifurcation thesis a sharper edge. The Chinese system is not just different; it is the picture of what a healthy state-supported middle market looks like. The contrast tells you what the Western middle is failing to be, and predicts where it goes from here.
| Western (US/FVEY) | Chinese (PRC) | |
|---|---|---|
| Supply structure | International, opaque, loosely affiliated networks. ~"Low hundreds" of individuals globally producing zero-day exploits at scale (per DeSombre). | Domestic, comprehensive feeder system: CTFs → universities → cybersecurity companies → MSS / MPS / PLA. Top-ten Chinese CTFs alone draw 11,000 participants on average; the US Cyber Open draws ~2,000. |
| Big Tech relationship | Strategic blocker. Apple, Google, Microsoft hardening is structurally opposed to the US offensive program. | Strategic enabler. QiAnXin, Huawei, Qihoo360, and NSFocus directly serve PLA / MSS. Internal "bespoke teams" feed exploitation research to government rather than to disclosure programs. |
| Procurement | Centralized, slow, risk-averse. Favors large primes (L3Harris, ManTech). Middlemen with prior government connections drive up costs and erode trust between buyers and sellers. | Decentralized to provincial and municipal level. iSoon held individual contracts with 56+ public-security bureaus equivalent in size to Cincinnati or Pittsburgh PD. "Guanxi" plus formal contracting; tolerated grey zone for cybercrime that aligns with state interests. |
| Disclosure regime | Voluntary CVD via vendor bug bounties. Researchers retain choice over disclosure path. | RMSV 2021 mandates 48-hour disclosure to MIIT; PoC code is encouraged. Chinese hackers were forbidden from foreign competitions in 2018; Pwn2Own participation dropped to zero. Chinese researchers still account for 27% of vulnerabilities reported to Apple/Google/Microsoft bounties 2017–2023, frequently from individuals with intelligence-apparatus links. |
| Cost discipline | "Feast-or-famine" contract cycles; long latency between bid and award; preference for exquisite stealthy capabilities raises unit cost. | Government deliberately depresses prices via monopsony; deep tolerance for noisy / detectable capabilities; n-day reuse extends asset shelf-life. "A-team to D-team" cascade: elite teams get first crack, then the same vulnerability is handed down through tiers of operators after initial use. |
| Burn discipline | "Burning" capability is a discrete, costly event. Operators select capability against observed defenses to preserve unburned chains. | Truly burning a capability is rare. Same exploit cascades through multiple groups before it's effectively retired. Microsoft Exchange 2021: vulnerability used by one APT group, then en masse by other Chinese groups within 24 hours of patch. |
| AI integration | Defensive-leaning (Big Sleep, AIxCC). Offensive AI tooling restricted by vendor guardrails. Defenders chilled by AI vendor policy (per Dowd, Section 4). | "Civil-military fusion" since 2017. Huawei's "HULK bot" (ML-enabled fuzzer) is a dominant Linux kernel contributor finding unknown vulnerabilities. Six Chinese universities with state-cyber links conduct cutting-edge offensive AI research since 2021. |
The DeSombre framing is sharp: "China's domestic cyber pipeline dwarfs that of the United States"; "China's acquisition processes use decentralized contracting methods... shortens contract cycles, and prolongs the life of an exploit through additional resourcing and 'n-day' usage"; "the United States risks ceding to China whatever strategic advantage it has left in cyberspace" without significant reform.
The Western middle market — boutique research firms below the L3Harris / NSO tier but above the Cellebrite "button" tier — is structurally weak in ways the Chinese middle is not. DeSombre's report names the mechanisms:
The Chinese middle market thrives because the state actively props it up: state-mandated vulnerability flow into CNNVD, decentralized provincial procurement that lets small firms close 56+ separate contracts, civil-military fusion that integrates corporate research teams as offensive capacity, and a deliberate "A-team to D-team" cascade that gives middle-tier operators access to depleted-but-still-useful capabilities. Without those mechanisms, the Western middle is a market segment defending itself against gravity. The bifurcation thesis (Section 7) is the consequence.
Net read: the trend toward thinning is observable. Whether it reaches collapse depends on whether the West adopts any of the structural mechanisms that prop up the Chinese middle. The Pall Mall Process is the strongest signal that Western policymakers see the gap; whether the procurement reforms follow is a 2026–2028 question.
If the Atlantic Council framing is right, the bifurcation in Section 7 is not just a market dynamic. It is a national-security capability gap. The Chinese model treats the middle as a strategic resource to be cultivated; the Western model treats it as an unfortunate side-effect of capitalism. DeSombre is direct: "It is impossible for the United States to match China's supply of zero-day exploits by sheer numbers alone." The path forward she proposes is not to copy the authoritarian funnel, but to selectively borrow the structural mechanisms — state-sponsored brokers, talent pipelines, decentralized procurement, n-day usage — that make the Chinese middle viable.
The 2026 Dowd interview, recorded around the same time as DeSombre's research, makes the same prediction from a practitioner's vantage:
"The less sophisticated the vendor, the more likely you are to be able to pop out a zero day with an LLM, and they're also the people less likely to patch it in a short space of time. The more sophisticated vendors are in a much better position to deal with this... as the cost of development goes towards zero, it's not that difficult for them to re-architect significant blocks."
The pincer is: at the top, AI accelerates defender re-architecture so chains get longer and more expensive (Section 4-5). At the bottom, AI commoditizes discovery against weak vendors (Section 9-10). In the middle — where the Western market is structurally weakest and the Chinese system is most actively cultivated — the gap widens until either the West adopts state-feeder mechanisms or the middle ceases to exist as a meaningful market segment.
That is the most consequential prediction this paper is willing to make. It is also the most falsifiable: by 2028, either the Pall Mall Process has produced a functional FVEY middle-tier broker, or the Western middle has consolidated into the prime-and-commodity duopoly that the bifurcation thesis describes. There is no stable third path.
The AI inflection's most concentrated harm may not land on hyperscale vendors at all. It lands on the long tail.
Net read: the IoT and edge half is well-documented; the "mid-tier SaaS most exposed" framing is a directional claim. The counter is real but measures exploited zero-days rather than discovered vulnerabilities — the two universes diverge under AI-assisted discovery.
Great-power exemplar: the December 2024 Treasury sanction on Sichuan Silence Information Technology documents the less-sophisticated-vendor problem at industrial scale. PRC contractor Sichuan Silence and Guan Tianfeng exploited Sophos firewall CVE-2020-12271 in April 2020, compromising 81,000 firewalls including 36 protecting US critical infrastructure operators. The vendor was not Apple. The vulnerability was not in MIE-protected code paths. The economics ran the other direction: a single bug in a mid-tier security appliance compromised more strategic surface than ten iOS zero-clicks would have. The pattern repeats with Salt Typhoon's exploitation of provider-edge and customer-edge routers (Cisco, Palo Alto), and with Volt Typhoon's living-off-the-land tradecraft against energy, water, and transportation sector edge devices. Hardened-mobile mitigation gains have pushed adversary attention down the vendor stack, and the less-sophisticated-vendor segment is where great-power competition is producing the most strategic damage.
"The less sophisticated the vendor, the more likely you are to be able to pop out a zero day with an LLM, and they're also the people less likely to patch it in a short space of time. So those particular vendors could potentially find themselves in a not very comfortable position depending on how much access they get to LLMs and what their pipeline is. The more sophisticated vendors are in a much better position to deal with this — and don't forget, as the cost of development goes towards zero, it's not that difficult for them to re-architect significant blocks of not just the vulnerable code but their patching infrastructure."
The asymmetry is a defender-side mirror of the buyer-side bifurcation. The top of the market gets a tailwind — more compute, more research budget, AI-assisted re-architecture. The long tail gets a headwind — AI-assisted discovery, no comparable patching pipeline, and an attacker class that has already shown it will target the path of least resistance.
No model of a market this opaque is right; the question is whether it is useful. This section names the load-bearing claims, what they get right, what they likely get wrong, and what cannot be priced at all from where this paper sits.
Every claim in this paper sits inside a US-China structural rivalry that is now reshaping the marketplace faster than the marketplace itself is moving. Forward-leaning claim C14 is the connective tissue:
Net read: the structural pressure is real and bidirectional. The 2024 trajectory was toward more state intervention; the late-2025 trajectory toward less. Anyone modelling the marketplace without modelling the political weather is using the wrong frame.
Dowd's "Wild West / manifest destiny" framing is the right rhetorical anchor:
"When I first got into hacking and the internet, one of the things I thought was awesome about it was I regarded it as a frontier — like a Wild West where stuff just happened, and I kind of liked the chaos to an extent. We're in this manifest-destiny period once again. Back then the stakes were pretty low because it was just a bunch of crap websites; now there's real security concerns particularly with people's personal devices, so it's more serious now. We've sort of known AI is coming for basically my entire career — every now and then on a podcast people would talk about the ethics of AI, what if it could do this or that, and they'd have this long drawn-out discussion, forget about it, have another one in six months. Then one day OpenAI and Anthropic and a few people said 'hey you can do this now, let's see what happens.' All of those discussions were just tabled — we'll just do it and then see what happens."
The honest position for any vulnerability-economics framework right now is: the variables we have priced are real, the variables we are pricing today will look quaint in 24 months, and the smart move is to publish what we know with confidence labels and let the next edition discipline the previous one. That is the discipline this paper attempts to model.
A research corpus of ~150 historical exploit / vulnerability / surveillance-product transactions (court records, leaked invoices, government disclosures, journalism) was compiled in April 2026 and used to stress-test the interactive model's algorithm. The full corpus lives at research/2026-04-25-confirmed-prices/RESEARCH.md; the algorithm validity report at VALIDITY-STRESS-TEST.md. The anchors below are the single most evidentiarily strong rows from that corpus — they are the empirical bedrock under every claim in this edition.
Full corpus: RESEARCH.md. Algorithm-validity scoreboard: VALIDITY-STRESS-TEST.md. Machine-readable subset: data/confirmed-prices-2026-04.json.
All sources cited inline above are reproduced here for ease of reference. Where multiple URLs share an institution, both are listed.
All citations independently verified at time of publication. Where a counter could not be found in authoritative sources (Claim C4), the absence is stated explicitly rather than fabricated.