Ask a room of security executives to name the last five capabilities their EDR vendor shipped and you will hear a familiar list. Better behavioral analytics. Faster correlation across identity and cloud telemetry. An AI copilot that triages tier one alerts. Automated response playbooks that isolate a host in seconds rather than minutes. Every one of those is a real improvement, and every one of them shares a single unstated assumption: that the malicious file already reached the endpoint, and the job is to catch what it does next.
Content Analysis, Disarm and Reconstruction (CADR) takes the opposite position. It assumes the file is guilty until proven structurally clean, decomposes it, discards anything that does not belong, and rebuilds a safe, usable version before it ever touches a user. There is no detection step because there is nothing left to detect. No signature. No behavioral model. No verdict. The threat is not caught, it is removed.
This is not a new idea, and it is not a fringe one. So the obvious question, the one investors ask within about ninety seconds of hearing the pitch, is this: if it works, why has CrowdStrike not built it? Why has Microsoft not built it? Why has SentinelOne, or Palo Alto, or Sophos, or any of the platform vendors with billion-dollar research budgets not simply absorbed the capability and moved on?
The answer is more interesting than incompetence, and considerably more durable.
One: Detection is the business model, not the outcome
Start with how the money actually moves. An EDR platform is sold on telemetry volume, alert fidelity, and analyst efficiency. An MDR service is sold on the number of events a human team will review on your behalf. An XDR platform is sold on the breadth of signals it can correlate. Every one of those metrics is a function of how much suspicious activity flows through the system.
Now consider what happens when a CADR layer is installed upstream. Weaponized documents stop arriving. Macro-laden spreadsheets stop arriving. Embedded scripts, malformed structures, exploit-bearing images, and script payloads hidden inside otherwise ordinary attachments simply stop existing by the time they reach the endpoint. The alert queue does not get better. It gets quieter.
For the buyer, that is the entire point. For the vendor whose renewal conversation is built around the value of the alerts they surfaced last quarter, it is an awkward thing to sell. A company does not typically build the product that makes its flagship product’s output less impressive. This is not conspiracy, and it is not bad faith. It is what incentive structures do to product roadmaps over a ten-year period, and it happens quietly, in prioritization meetings, one deferred feature at a time.
Two: They are architecturally in the wrong place
This one is structural rather than commercial, and it is probably the most underappreciated of the six.
An EDR agent lives on the endpoint. It hooks the kernel, watches process creation, monitors memory, and observes what code does once it is running. That vantage point is genuinely excellent for what it is designed to do. It is also, by definition, downstream of the file’s arrival. By the time the agent has an opinion, the file is on the disk of a machine inside your perimeter.
CADR belongs somewhere else entirely. It belongs at the mail gateway, at the web proxy, at the file upload endpoint of a customer portal, at the ingestion point of a document management system, at the boundary of a shared drive, and increasingly at the entrance to a retrieval pipeline feeding an AI model. Those are transit points, not endpoints. Serving them requires a different deployment architecture, a different set of integration partners, a different performance profile, and a different engineering discipline than shipping an agent to two hundred thousand laptops.
A vendor with a world-class endpoint agent does not automatically have a world-class file transit engine, any more than a company that builds excellent car alarms automatically knows how to build a bridge. The muscles are different. And once an organization has spent a decade optimizing for one, retooling for the other is expensive, slow, and internally unpopular.
Three: Reconstruction carries a liability profile detection vendors do not want
Here is the part that keeps product managers at large platform vendors awake, and it is worth stating plainly because it is a real objection and it deserves a real answer.
When a detection engine is wrong, the consequence is a false positive. An analyst wastes twenty minutes. Someone grumbles. The vendor tunes a rule and the incident is forgotten by Thursday. The failure is annoying and it is recoverable.
When a reconstruction engine is wrong, the consequence is that the finance director’s quarterly model stops calculating, or the architect’s drawing loses a layer, or the legal team’s redlined contract arrives with its tracked changes silently flattened. That is not an annoying failure. That is a failure that generates an executive escalation, and it lands on the vendor who touched the file.
A platform vendor with a hundred thousand enterprise customers is deeply, rationally reluctant to introduce a capability whose failure mode is corrupting the customer’s own documents. So they do not build it. They stay in the business of having opinions about files rather than the business of rebuilding them.
That reluctance is exactly the moat. The hard engineering problem in CADR is not only identifying that a macro is dangerous. Most cybersecurity gurus can do that. The hard problem is rebuilding a hundreds file formats with enough fidelity that the CFO never notices anything happened. That is deep, unglamorous, format-by-format work, accumulated over years, and it is not something a platform vendor can spin up in two quarters because it decided the category looked attractive. It is precisely the kind of durable technical asset that does not show up on a feature comparison chart but cannot be replicated by a bigger balance sheet alone.
Four: The category was filed under someone else’s name a decade ago
Markets are shaped by taxonomy, and taxonomy is sticky.
The lineage of disarm-and-reconstruct technology runs through a set of vendors who positioned it, quite reasonably at the time, as an email security feature. It got catalogued as a gateway add-on. It appeared as a checkbox in secure email gateway comparisons. And once a capability has been filed under a category, the buying committee stops looking for it anywhere else. The CISO evaluating endpoint platforms does not ask whether the endpoint platform disarms files, because disarming files is, in the mental model the industry handed them, an email thing.
Meanwhile the actual threat surface moved. Files no longer arrive primarily by email. They arrive through customer upload portals, through collaboration platforms, through third party integrations, through partner data exchanges, through supply chain document flows, and now through the ingestion pipelines feeding retrieval-augmented AI systems. The old category boundary was drawn around a channel that no longer represents most of the risk, and nobody has redrawn it.
That mismatch is a market gap in the most literal sense. The capability is understood. The threat has moved. The category has not followed. When large platforms eventually notice, their historical pattern is unambiguous: they do not build, they acquire, and they acquire the company that owns the technology and the reference customers.
Five: The industry’s attention is pointed the other way
Every dollar of security research and marketing spend right now is chasing a single narrative: the autonomous SOC. The AI analyst. The agent that triages, correlates, investigates, and responds without a human in the loop.
Read that narrative carefully and notice what it is. It is detection, made faster. It is the same fundamental posture, executed with more compute. The premise remains that threats will arrive, that alerts will fire, and that the winning move is to process them more intelligently.
Prevention-first is an unfashionable argument in a market that has just spent billions funding a better response function. It does not fit the slide. It does not fit the demo. It is difficult to build a compelling stage presentation around the absence of an incident. And so the industry’s collective attention has drifted steadily further from the front door.
Note the second-order effect, because it matters. The same generative AI wave that is making the SOC faster is making the attacker’s file cheaper. Malware-as-a-service operations now generate novel, polymorphic, structurally-varied payloads at a marginal cost approaching zero. The volume of never-before-seen files is rising faster than any detection model’s ability to have seen them before. A defense predicated on recognition is being asked to keep pace with an offense that has industrialized non-recognition. That race has an arithmetic that does not favor the defender, and it is the strongest argument available for a control that does not need to recognize anything at all.
Six: The scorecards do not measure it
Vendors optimize for the tests they are graded on, and the tests in this industry are all built around detection.
Adversary emulation evaluations score whether a product generated telemetry for a given technique, whether it produced an alert, and how much analyst context that alert carried. Independent lab tests measure detection rate and false positive rate. Analyst grids weight response capability, investigation workflow, and threat hunting depth. Every one of those frameworks presupposes a product whose job is to notice things.
A product that neutralizes a weaponized document such that the technique never executes does not score well on a matrix of techniques, because it does not participate in the matrix. It removes the file. There is no telemetry to generate, because nothing happened. On a detection scorecard, a perfect prevention outcome is indistinguishable from a product that was not installed.
This creates a genuinely perverse dynamic. The measurement infrastructure of the entire industry is structurally incapable of rewarding the outcome the industry claims to want. Vendors respond to that incentive exactly as you would expect. They build for the test.
What this means for the board
Assemble the six and a fairly uncomfortable picture emerges, and it is worth putting to a board in plain language.
The detection, response, and managed security industries are, structurally, downstream of a failure that has already occurred. Their entire value proposition activates at the moment a hostile file has already reached an asset you own. Their revenue, their metrics, their evaluation frameworks, and their product roadmaps are all calibrated to that moment. This is not a criticism of their competence. Detection vendors are, in general, extraordinarily good at detection, and no serious security program should be without it.
But an industry cannot be relied upon to eliminate the condition it is paid to manage. That is not cynicism. It is simply how commercial incentives compound over time, and it explains, more completely than any technical argument, why a capability with a decade of proven engineering behind it remains conspicuously absent from every major platform’s core offering.
The strategic question for a board is therefore not whether the organization‘s detection stack is good. It very probably is. The question is whether the organization has any control anywhere in its architecture whose success condition is that the alert never fires. If the honest answer is that every dollar of file-borne threat spend is allocated to products that only earn their keep after the file has arrived, then the security program has a structural dependency on being fast enough, every single time, forever. That is a defensible position right up until the first time it is not.
What this means for an investor
The investment thesis reduces to a single sentence. A large, well-capitalized, technically sophisticated set of incumbents has spent a decade choosing not to build a capability that their own customers increasingly need, and every one of the reasons they made that choice is durable rather than temporary.
Their revenue model discourages it. Their architecture is in the wrong place for it. Their liability tolerance forbids it. Their category taxonomy has assigned it to someone else. Their attention is committed elsewhere. And their scoreboards cannot reward it. Those are not conditions that reverse in a quarter because a competitor put out a press release. They are the accumulated shape of an industry.
Meanwhile the underlying demand is moving in exactly one direction. File volume is rising. File-borne attack sophistication is being industrialized by generative tooling. The ingestion surface is expanding from email into upload portals, collaboration platforms, supply chain exchanges, and AI training and retrieval pipelines. Regulators and insurers are beginning to ask, with increasing pointedness, what preventative controls exist rather than what detection coverage exists.
A market gap that persists because incumbents cannot profitably close it is worth considerably more than one that persists because nobody has noticed. This one is the former.
FileDNA applies Content Analysis, Disarm and Reconstruction at the point of file entry, decomposing every inbound file, removing active and anomalous content, and rebuilding a clean, fully usable version before it reaches a user, a system, or a model. No signature. No verdict. No alert. The threat is not detected. It is gone.
Disclaimer
The analysis presented in this article represents the opinion and commercial perspective of CyberQuay, Inc. It is offered as strategic commentary on the structure and incentives of the endpoint and extended detection markets, and it should be read as such rather than as a statement of fact about the intentions, internal roadmaps, or product decisions of any named company.
CyberQuay holds the detection, response, and managed security vendors referenced below in high regard. The engineering behind modern EDR, MDR, and XDR platforms is genuinely world class, and the outcomes those platforms deliver are real, measurable, and indispensable. Nothing in this article should be read as an assertion that these products are ineffective, poorly built, unnecessary, or of diminished value. They are none of those things, and no serious enterprise security program should attempt to operate without them.
Our argument is one of layering rather than replacement. Detection and response answer the question of what to do once a threat is present in the environment. Content Analysis, Disarm and Reconstruction answers a different and prior question, which is whether the threat needs to be present at all. These are complementary controls addressing different points in the same attack chain. CADR does not compete with EDR, XDR, or MDR. It reduces the volume of file-borne material those platforms are asked to reason about, so that their considerable analytical capability can be applied to the threats that genuinely require it. A well-designed security architecture benefits from both.
The observations regarding commercial incentives, architectural positioning, category taxonomy, and evaluation methodology are structural in nature. They describe forces that act on organizations over time rather than choices made by individuals, and they are not intended to impute bad faith, negligence, or any deliberate withholding of capability on the part of any vendor. Reasonable and well-informed people disagree on these points, and CyberQuay welcomes that disagreement.
CyberQuay, Inc. has no commercial relationship with, and no financial interest in, any of the companies named in this article. Product capabilities described are drawn from vendors’ own public documentation as of the date of publication and may change. Readers are encouraged to consult the primary sources listed below and to evaluate all claims, including ours, on their own merits.
All product names, trademarks, and registered trademarks referenced in this article are the property of their respective owners, and their use here is for identification and commentary purposes only. This article does not constitute investment advice, and it should not be relied upon as the basis for any investment decision.
References
The following are the official vendor pages for the endpoint detection, extended detection, and managed detection platforms discussed in this article. Readers are encouraged to review them directly.
Endpoint and extended detection and response platforms
CrowdStrike, Falcon Insight XDR.
https://www.crowdstrike.com/en-us/platform/endpoint-security/falcon-insight-xdr/
CrowdStrike, Endpoint Security overview.
https://www.crowdstrike.com/products/endpoint-security/falcon-insight-xdr/
Microsoft, What is Microsoft Defender XDR.
https://learn.microsoft.com/en-us/defender-xdr/microsoft-365-defender
Microsoft, Defender products and services.
https://learn.microsoft.com/en-us/defender/
SentinelOne, Singularity XDR Platform.
https://www.sentinelone.com/platform/singularity-xdr-protection/
Palo Alto Networks, Cortex XDR.
https://www.paloaltonetworks.com/cortex/cortex-xdr
Palo Alto Networks, Cortex endpoint detection and response.
https://www.paloaltonetworks.com/cortex/endpoint-detection-and-response
Sophos, Endpoint powered by Intercept X.
https://www.sophos.com/en-us/products/endpoint-antivirus
Managed detection and response services
CrowdStrike, Falcon Complete Next-Gen MDR.
https://www.crowdstrike.com/en-us/services/falcon-complete-mdr/
Microsoft, Defender Experts for XDR.
https://learn.microsoft.com/en-us/defender-xdr/dex-xdr-overview
Microsoft, Defender Experts MDR.
https://learn.microsoft.com/en-us/defender-xdr/defender-experts/defender-experts-mdr-overview
Palo Alto Networks, Cortex platform including Unit 42 Managed Detection and Response.
https://www.paloaltonetworks.com/cortex
Sophos, Managed Detection and Response.
https://www.sophos.com/en-us/services/managed-detection-and-response
Category definitions and evaluation frameworks
CrowdStrike, What is XDR. Vendor explainer including the Gartner definition of extended detection and response.
https://www.crowdstrike.com/en-us/cybersecurity-101/endpoint-security/extended-detection-and-response-xdr/
MITRE Engenuity, ATT&CK Evaluations. The adversary emulation framework referenced in the discussion of detection-oriented scorecards.
https://attackevals.mitre-engenuity.org/
MITRE, ATT&CK knowledge base.
https://attack.mitre.org/
All vendor pages accessed and verified July 2026. Product names and capabilities reflect vendor documentation as published at that time and are subject to change.