Application security,
remediated by agents.

A CIO and CISO guide to AI-powered, agentic application security. Why the vulnerability backlog became the breach, what code security, software composition analysis, supply chain, runtime and posture management each cover, and how Axiarete's agents find, qualify, fix and verify vulnerabilities across the whole estate under human approval.

Axiarete AI·Published ·27 min read

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An estate's vulnerabilities: found, qualified, fixed, verified. Illustrative.
Finding

In brief. Application security is the discipline of finding and removing exploitable weaknesses in the software an enterprise builds, buys and runs: in its own code, in the open-source and third-party components it depends on, in the supply chain that delivers them, in the infrastructure and containers that host them, and in their behaviour at runtime. The tools exist for every layer and the backlog they produce has outgrown every team. Agentic application security, the form of AI-powered application security in which the agents carry the work rather than assist it, changes the shape of the program: AI agents hold one picture of the estate across every layer, qualify each finding against reachability, exposure, exploitation in the wild and the business process it sits under, draft the fix, raise it through the organization's own pipelines and change control for a named person to approve, and verify closure. Axiarete AI operates this model today and is already remediating in Fortune 500 production environments.

Five things to take from this guide

  1. Exploited vulnerabilities are now the way in. Verizon's 2025 Data Breach Investigations Report found exploitation of vulnerabilities behind 20% of breaches, up 34% in a year, and third-party involvement doubled to 30%.
  2. The supply chain is the estate. Black Duck's 2025 analysis of 965 commercial codebases found 86% contained vulnerable open-source components, 81% with high- or critical-risk vulnerabilities, and 90% with components more than four years out of date.
  3. The gap is not detection. Organizations fully remediated only about 54% of edge-device vulnerabilities in a year, at a median of 32 days each, while exploitation of the same class of devices grew almost eightfold. The backlog is closed by fixes, and fixes are the constraint.
  4. Agentic application security has four defining properties: one picture across every layer; findings qualified by reachability, exposure, exploitation and business context; agents that fix under human approval, through the organization's own change control; and verification of closure.
  5. Axiarete customers report more than 100 critical risks discovered and remediated across a decades-old estate, with 50 to 80 percent less engineering effort per issue, and discovery-to-fix reduced from months to days.

The attack surface has outgrown the tools

"What Axiarete has delivered in just 2 weeks, with very little effort from us, is truly incredible. We never had this level of intelligence in our portfolio — or the know-how to reduce technical debt."Enterprise Technical Debt Program Leader, Fortune 100 financial services

Every CISO runs a version of the same program: scanners on the code, scanners on the dependencies, scanners on the containers and the cloud, a dashboard that correlates them, and a backlog measured in thousands that grows on every release. The program is not failing for lack of findings. It is failing because findings are not risk, because the fix is an engineering task that belongs to no one, and because the estate the scanners cover is not the estate that is actually running.

20%of breaches begin with an exploited vulnerability, up 34% year over yearVerizon DBIR 2025
30%of breaches involve a third party, double the prior yearVerizon DBIR 2025
86%of commercial codebases contain vulnerable open source; 81% high or criticalBlack Duck OSSRA 2025
32 daysmedian time to remediate an edge-device vulnerability; only ~54% fully remediated in a yearVerizon DBIR 2025

The numbers describe a single shift. Attackers moved from tricking people to exploiting software, and the software they exploit is increasingly software the enterprise did not write: open-source libraries, vendor components, edge devices, build pipelines. Verizon's analysts recorded exploitation of edge devices and VPNs rising from 3% to 22% of vulnerability-exploitation incidents in one year; against a median remediation time of 32 days, that is a window attackers no longer need. Black Duck's audit team found open source in 97% of the codebases it examined, and vulnerable open source in 86%. Gartner's guidance on Application Security Posture Management predicted that more than 40% of organizations developing proprietary applications would adopt ASPM by 2026, an acknowledgement that the tools had multiplied faster than the ability to make sense of them.

Behind the percentages sit two facts that decide whether a program works. The exposure lives in the running estate rather than the scanned one; in Axiarete's own review of fifty major incidents, the compromised system in many of the authentication-related cases had never appeared in an inventory. And the constraint is remediation, not discovery. A program that finds more findings will not close the gap. A program that ships more fixes will.

What application security covers in 2026

Application security is the discipline of finding and removing exploitable weaknesses in the software an enterprise builds, buys and runs, across its own code, its dependencies, its supply chain, its infrastructure and its behaviour at runtime. Each of those is a distinct surface with its own tooling and its own vocabulary, and the vocabulary is worth being precise about, because most programs are sized by the surface they can see rather than the surface they have.

Code security SASTWeaknesses in the application's own source: injection, broken authentication, unsafe deserialization, hard-coded secrets. Static application security testing finds patterns; the work is telling an exploitable path from a match.
Dependencies SCASoftware composition analysis: the open-source and third-party components an application ships, their versions, known vulnerabilities and licenses. Most of the code in most applications.
Supply chain SBOM · AIBOMThe path by which code reaches production: registries, build pipelines, container images, vendor components, and now the models and datasets an application calls. The bill of materials is the inventory it depends on.
Infrastructure and containers IaCThe hosts, images, orchestration and cloud configuration the application runs on. Misconfiguration here exposes correct code.
Runtime security RUNTIMEWhat is actually executing: which services, what they load, what they connect to, and whether their behaviour departs from what is expected. The layer that turns theoretical findings into real ones.
Posture ASPMApplication security posture management: the correlation of every layer's findings into one view, with context, ownership and workflow. Necessary, and, on its own, a better-organized list.

The layers are usually bought separately, staffed separately and reported separately, and the seams between them are where exposure hides: the library that SCA flags but runtime shows is never loaded; the correctly written service that a container misconfiguration exposes to the internet; the vendor component nobody scanned because nobody knew it was there. Posture management was created to close those seams by correlating the tools, and it does, on the dashboard. Closing them in the estate is a different job.

Findings are not risk: vulnerability management by qualification

The most consequential fact in application security is also the least visible in the tooling: the large majority of findings are not exploitable in the deployed system. A vulnerable library that is never loaded, a code path no request can reach, a service with no route from the internet, a CVE with no known exploit: each is a finding, none is the exposure a reachable, internet-facing, actively exploited vulnerability under a revenue-carrying process is. The illustration below shows what happens to a typical backlog when findings are qualified rather than counted.

When the backlog becomes the breach

The mechanism is rarely a novel exploit. Far more often it is a known vulnerability in a system that was running, and that was already on someone's list.

  • Equifax, 2017: a patch available for two months

    Apache disclosed a critical vulnerability in the Struts framework on 7 March 2017 and released the fix the same day. Equifax's own security team circulated an instruction to patch within 48 hours. The instruction did not reach the team responsible for the consumer dispute portal, the portal was not patched, and in May attackers used the vulnerability to take the personal data of roughly 147 million people. The settlement with the FTC, the CFPB and the states ran to at least $575 million. Nothing about the vulnerability was unknown: the patch existed, the alert went out, and the one system that needed it sat outside the process that was meant to reach it.

  • Log4Shell, 2021: the component nobody could locate

    In December 2021 a trivially exploitable flaw was disclosed in Log4j, a logging library embedded in a large share of the world's Java software. The difficulty for most enterprises was not the patch, which existed within days. It was establishing where the library ran: which applications, which vendor products, which containers, which build pipelines. Organizations that had a current bill of materials for their estate closed the exposure in days. Organizations that did not spent months, and some are still finding instances. What separated the two groups was an inventory, and nothing more sophisticated than that.

  • MOVEit, 2023: one vendor component, thousands of victims

    A single vulnerability in a widely used managed file transfer product was exploited by one criminal group across, by Emsisoft's count, more than 2,700 organizations and the records of over 90 million people, most of whom had never heard of the product because it sat inside a supplier's stack. The exposure was not in code any of the victims wrote. It was in a third-party component in their supply chain, which is precisely the class of exposure Verizon now records as doubling.

Axiarete's own review of fifty major security incidents between 2020 and 2025 found the same pattern from the other direction: two control failures, unpatched internet-facing software and broken authentication, accounted for just over half of the set, and in many of the authentication cases the compromised system was not known to be in use at all. The full analysis is here. The common factor is not sophistication. It is a known weakness, in a running system, that the program could not see or could not reach.

Why enterprises cannot close the backlog with the tools they have

The application security backlog persists for five structural reasons, none of which is a shortage of scanners.

  • 1. Findings are counted, not qualified

    A backlog of twelve thousand equally weighted items is not a plan. Without knowing which findings are in code that runs, reachable, exposed to the internet, exploited in the wild and under a process the business depends on, teams work the list by severity score, which is to say they work the wrong list.

  • 2. The fix belongs to no one

    Security finds; engineering fixes; and the fix competes with the roadmap. Every vulnerability is a ticket handed to a team that did not create it and is not measured on closing it. The 32-day median measures ownership far more than it measures difficulty.

  • 3. One tool per layer, no single picture

    Code, dependencies, containers, cloud and runtime are scanned by different products with different identifiers, so the same exposure appears as five findings or as none. The seams between tools are where the breach-grade exposure sits, and posture dashboards correlate the findings without changing the fact that no tool holds the whole.

  • 4. The scanned estate is not the running estate

    Scanners cover what they are pointed at. The systems that appear in no inventory, the forgotten portal, the vendor appliance, the service someone stood up in 2019, are the systems nobody points a scanner at, and they are disproportionately where breaches begin.

  • 5. The exploitation window closed faster than the remediation window

    Working exploits now follow disclosure within days, and a growing share of edge-device vulnerabilities are exploited before a patch exists at all. Against that, a program whose median remediation is a month is always behind, and better prioritization does not change the arithmetic while the fix itself still takes a month to ship.

Read together, the five bottlenecks describe one job: hold a current picture of a large estate, judge every finding against context that no single tool has, and push fixes through engineering faster than the disclosures arrive. No security team has ever been staffed for that job, which is why it has never been done. It is, however, exactly the kind of sustained, context-heavy work that AI agents can now carry.

The exploitation window, and the remediation window

Days from disclosure to first observed exploitation have collapsed; days from disclosure to remediation in the average enterprise have not moved. The shaded gap is the period during which a known vulnerability is exploitable in production, and it is the period an agentic program exists to close.

EarlierNow Days after disclosure Time to remediate: about a month, unchangedTime to exploit: days, and fallingThe exposure window
Where the risk sits. Illustrative curves, consistent with Verizon's reported median of 32 days to remediate edge-device vulnerabilities and with public exploitation now routinely following disclosure within days. Prioritization narrows what is in the window; only faster fixing narrows the window itself.

What agentic application security actually means

Agentic application security is a program in which AI agents hold one picture of the estate across every layer, qualify each finding against reachability, exposure, exploitation in the wild and the business process it sits under, draft the fix, raise it through the organization's own pipelines and change control for a named person to approve, and verify closure. It is neither a scanner with a language model attached nor a posture dashboard with better ranking. Both are useful. Neither closes the backlog, because backlogs are closed by fixes.

The distinction from AI-powered vulnerability management also matters. Applying AI to triage, to explain findings and to suggest patches is a real improvement on manual work and leaves the structure intact: separate tools, an unowned fix, a month to ship. Four properties distinguish an agentic program from an AI-assisted one.

One picture across every layer. Code, software supply chain, runtime, containers, infrastructure and secrets are assessed in one native picture of the estate, assembled from what the systems themselves show rather than from separate tools' exports, and including the systems that appeared in no inventory. The same vulnerability is one exposure, located, rather than five findings or none.

Every finding qualified, including against the business. Each finding is tested against whether the component is loaded, whether the path is reachable, whether the service is exposed, whether exploitation has been observed, and, distinctively, which business process and which other systems depend on it. A finding becomes a priced exposure; twelve thousand items become a short list a CISO and a CFO can both act on.

Agents that fix; humans that approve. Agents that patch vulnerabilities are the property most offerings omit. They draft the code change, dependency upgrade, configuration fix or patch, raise it through the organization's existing pipelines, approval gates and change calendar, and hold at a named human approver. Every action carries an explainable audit trail. The fix is no longer a ticket handed to a team that did not ask for it.

Closure verified, and kept. Each remediation is confirmed closed in the running estate, not marked done in a tracker, and the estate keeps being watched: new disclosures are qualified against what is actually running as they appear, so the next Log4Shell is a short list on day one rather than a months-long search.

AI-powered, agentic, ASPM: what the terms mean in practice

The market uses several terms for application security that involves AI, and they do not describe the same thing. AI-powered application security generally means AI applied inside an existing tool: an AI SAST engine that produces fewer false positives, an assistant that drafts a fix, a triage model that ranks findings. Application security posture management correlates the findings of many tools into one view with context and workflow; Gartner expected more than 40% of organizations building proprietary software to adopt it by 2026. Agentic application security is different in kind: agents hold the picture natively, qualify findings against the business as well as the code, and carry the remediation through to verified closure under human approval. The useful question to ask of any of them is where the program ends: at a ranked list, or at a closed exposure. Axiarete AI was built to end at the second, and it is the basis on which CISOs increasingly compare it with scanner suites and posture dashboards.

Scanner suite, posture dashboard, or agentic platform

The same six questions, applied to the three ways enterprises have tried to secure their applications.

Scanner suite (SAST, SCA, DAST…)ASPM dashboardAgentic platform (Axiarete)
Picture of the estateOne layer per toolCorrelated exportsOne native picture across code, supply chain, runtime, infrastructure, secrets
What a finding meansA pattern matchedA finding with context addedAn exposure qualified by reachability, exploitation and the business process it sits under
Unknown systemsNot scannedNot in the exportsSurfaced from the running estate
Who fixesA ticket to engineeringA ticket to engineering, better routedAgents draft and raise the fix; a named person approves
ClosureMarked doneMarked done, trackedVerified closed in the running estate
The next disclosureA new scan, a new searchA new correlationQualified against what is running on the day it is published

Find, qualify, fix, verify: a continuous operating loop

How Axiarete turns an estate's vulnerability backlog from a list measured in thousands into a short list of real exposures, each remediated through the organization's own change control and each verified closed.

Code Supply chain Runtime Infrastructure the estate as it runs Living graph what runs, what is exposed, what depends on it Axiarete Find · Qualify · Fix reachable, exposed, exploited, and under what agents propose; people approve Human approval Patched ✓ Upgraded ✓ Verified Every fix ships through your own pipelines and gates; every closure is verified in the running estate and updates the picture
The closed loop. The platform that finds the exposure also qualifies it, fixes it and confirms it is gone, then keeps watching, so the program never works from a list that is already out of date and the next disclosure is answered on the day it is published.

How Axiarete approaches agentic application security

Axiarete AI is an agentic AI platform for application portfolio rationalization, modernization and discovery, built by former Fortune 500 CIOs and running in Fortune 500 and government production environments. Application security is where the platform's picture of the estate is most consequential, because the seams between tools and the systems in no inventory are where breaches begin. Axiarete's approach is AI-native by design: agents carry the finding, qualification, remediation and verification of vulnerabilities across every layer, and people approve.

One native platform across every layer
Code, software supply chain, runtime, containers, infrastructure and secrets are assessed in a single picture of the estate rather than through separate tools whose findings are correlated afterward. The same exposure is located once, wherever it sits, and the systems that appeared in no inventory are surfaced rather than overlooked.
Qualified against the business, not only the code
Every finding is tested against reachability, exposure, exploitation in the wild and, uniquely, the business process it sits under and the portfolio that depends on it. The result is a short list of priced exposures that a CISO and a CFO read the same way, rather than a backlog ranked by severity score.
Agents that fix; people that approve
Agents draft the code change, dependency upgrade, configuration fix or patch, raise it through the organization's own pipelines, approval gates and change calendar, and hold at a named human approver. Every action carries an explainable audit trail, and closure is verified in the running estate rather than marked in a tracker. Axiarete is already remediating in Fortune 500 production.
The bill of materials, kept current
A software bill of materials and an AI bill of materials for the estate, maintained as the estate changes, with license compliance and zero-day monitoring against them, so that a new disclosure is answered with a list of affected running systems on the day it is published rather than after a search.
Nano sprints that eliminate a class of exposure
Remediation is scoped to the outcome rather than the calendar: a nano sprint removes one class of vulnerability across the estate, an end-of-life runtime, a family of vulnerable dependencies, a pattern of misconfiguration, with outcomes, SLAs and duration fixed in writing before delivery begins. The first verified remediation is delivered within the first weeks.
Workflows, SLAs and a management workspace
Findings, owners, approvals and deadlines are managed in one workspace with alerts and SLAs, so the program is run rather than reported, and the board sees exposure closing over time in the terms the business uses.
AxiareteForge: execution capacity, delivered as a product
Detection was never the constraint; the capacity to fix was. AxiareteForge addresses it as services-as-software: forward-deployed architects scope each engagement against the live picture of the estate; forward-deployed engineers deliver alongside the agents from week one. Nano sprints eliminate a class of technical risk, micro engagements capture remediation quick wins, and long-term programs carry security, modernization and portfolio optimization as one motion.
Governed by design
A platform that changes production systems must pass an information security review before it changes anything: SOC 2 Type II, ISO 27001 and ISO 42001 certified, HIPAA compliant, dedicated tenancy per customer, zero customer code or data used in model training, explainable outputs with a complete audit trail, and mandatory human-in-the-loop for every decision that touches the estate. Read the governance model.

Proof: what changes when vulnerabilities are remediated by agents

Results reported by Axiarete customers. Customer identities are withheld under NDA. See the full customer impact page.

FindThe whole estate's exposure in one picture, including the systems in no inventory.
QualifyEvery finding tested against what runs, what is reachable, what is exploited and what the business depends on.
Fix and verifyAgents raise the fix through your change control; a named person approves; closure is confirmed in the running estate.
  • Fortune 100 financial services

    Critical technical risk identified and remediated

    A decades-old legacy footprint carried critical risks conventional tools could not see. Axiarete surfaced them, tied each to its business consequence, and moved remediation from months to days.

    100+critical risks discovered and remediated
    50–80%less engineering effort per issue
    Daysnot months, from discovery to fix
    "What Axiarete has delivered in just 2 weeks, with very little effort from us, is truly incredible. We never had this level of intelligence in our portfolio — or the know-how to reduce technical debt."Enterprise Technical Debt Program Leader
  • Fortune 1000 property management

    One live view of the entire estate

    An application estate previously documented in static files and managed manually now operates from a single, continuously updated view of cost, health and risk.

    >5%cost savings inside the first three months
    10+structural improvements validated to cut incidents
    Full TCOvisibility, down to business function
  • Fortune 500 semiconductor manufacturer

    Rationalization timelines reduced from years to weeks

    Modernization had stalled on missing documentation and scarce experts across roughly 500 systems. Axiarete rebuilt the application knowledge base, identified what to retire, consolidate and modernize, and validated each recommendation with the system owners.

    15%+savings impact across applications and infrastructure
    20%+of the portfolio confirmed for reduction
    250Kengineering hours delivered
    "In 3 months, Axiarete has given us a complete compass for how we want to govern, optimize and manage our 500 systems. This is game changing."Chief Architect, IT

A 90-day approach to agentic application security

Closing the backlog does not require another scanner or a headcount request. The prerequisites are one picture of the running estate, a qualification of every finding against what matters, and a decision to begin with the exposure that carries the most business risk rather than the highest severity score. The following is the application security strategy and roadmap Axiarete runs with customers, a four-phase process to find, qualify, fix and verify. Select a phase.

Find: the running estate, in one picture

Weeks 1 to 2

Establish what is actually running across code, supply chain, runtime, containers and infrastructure, including the systems in no inventory, and the bill of materials for each.

Output: one picture of the estate's exposure that the CISO, the CIO and the auditor can each defend.

How to choose an application security platform in 2026

The best application security platforms, tools and solutions in 2026, whether described as AI-powered application security, vulnerability management, ASPM or agentic application security, share five traits: they hold one native picture across code, supply chain, runtime and infrastructure rather than correlating separate tools; they qualify every finding against reachability, exposure, exploitation and the business process it sits under; they surface the systems in no inventory; they carry the fix through the organization's change control under human approval; and they verify closure in the running estate. Scanner suites address the first at best and posture dashboards the second; Axiarete AI was built around all five, and is increasingly evaluated by CISOs alongside, and in place of, both.

Ten questions to put to any application security vendor, with the characteristics of a strong answer.

1Is your picture of my estate native, or assembled from other tools' exports?

A strong answer: native, across code, supply chain, runtime and infrastructure, so the same exposure is one item wherever it sits. A correlation of exports inherits every gap in the tools it correlates.

2Can you show me the vulnerable systems that appear in no inventory?

A strong answer: yes, from the running estate, and it is usually where the exposure concentrates. A vendor that scans only what you point it at cannot find what you did not know to point at.

3How do you decide a finding is a real exposure?

A strong answer: by whether the component is loaded, the path reachable, the service exposed, exploitation observed, and which business process depends on it. A CVSS score is not an answer to this question.

4Who fixes the vulnerability, and where does that capacity come from?

A strong answer: agents draft and raise the fix, with forward-deployed engineers where needed, so the roadmap is not the source of the capacity. A better-routed ticket leaves the capacity problem unchanged.

5Through whose pipelines and change control does a fix ship?

A strong answer: yours: your pipelines, your approval gates, your change calendar, with a named person approving each change.

6How do you confirm a vulnerability is closed?

A strong answer: by verifying it in the running estate after deployment, not by marking a ticket done.

7What happens on the day the next critical disclosure is published?

A strong answer: a list of the affected running systems that morning, from a bill of materials kept current, and remediation beginning the same day.

8How do findings become something my CFO and my board will act on?

A strong answer: every exposure is tied to a business process, a cost and a consequence, automatically, and the board sees exposure closing over time in those terms.

9What is the AI's role: recommend, or act under approval? Is every action auditable?

A strong answer: agents act, a named person approves, and every action carries an explainable audit trail an auditor can follow.

10Do you train on customer code? Where does my code reside, and who can reach it?

A strong answer: customer code and data are never used for training; each customer runs in a dedicated tenant under published certifications, with a security package available on request.

Application security is the precondition for AI agents in production

Every enterprise now intends to put AI agents to work inside its systems, and every such agent inherits the exposure of the estate it runs in: the unpatched library it calls, the misconfigured service it connects to, the vendor component in its path. An agent with authority to act in an estate whose vulnerabilities are unqualified and unremediated is not an efficiency; it is an amplifier.

This is why application security done agentically is not a cost to be paid before AI but the first AI program that makes the others safe. The same picture of the running estate that locates and qualifies exposure is the context every other agent needs in order to act with confidence, and the same governance, a named approver, an audit trail, changes through the organization's own controls, is the governance every other agent should inherit.

The first agent to put in production is the one that closes the exposure the others would inherit.

Frequently asked questions about AI-powered and agentic application security

What is AI-powered application security?

AI-powered application security uses AI to improve parts of an existing security program: triaging scanner findings, summarizing vulnerabilities, suggesting fixes in code. It is a meaningful improvement on manual triage and does not change the shape of the program: the findings still arrive from separate tools, the fix is still an engineering task no one owns, and the backlog still grows faster than it closes.

What is agentic application security?

Agentic application security is a program in which AI agents carry the work end to end: they build one picture of the estate across code, software supply chain, runtime, containers, infrastructure and secrets; qualify every finding against reachability, exposure, exploitation in the wild and the business process it sits under; draft the fix; raise it through the customer's existing pipelines and change control for a named person to approve; and verify closure. Axiarete AI operates this model today, remediating in Fortune 500 production environments.

Can AI agents patch vulnerabilities?

Yes, within governance. Agents can locate a vulnerable component, determine whether it is reachable and exposed, prepare the patch or code change, raise it through the organization's pipelines and approval gates, and verify that the vulnerability is closed after deployment. Responsible platforms do not deploy without approval: a named person approves each change and every action carries an audit trail. What changes is the pace: the patch is prepared, raised and verified in hours rather than waiting weeks in a queue.

What is AI-powered vulnerability management?

AI-powered vulnerability management applies AI to the vulnerability lifecycle: discovering what is running, qualifying which findings are real and reachable, prioritizing by exploitation and business impact, and, in an agentic program, remediating and verifying the fix. The distinction that matters is whether the AI stops at a better-ranked list or carries the fix through, because the backlog is closed by fixes, not by rankings.

What is AI SAST, and how does it differ from traditional static analysis?

Static application security testing (SAST) analyzes source code for vulnerable patterns. Traditional SAST produces large volumes of findings, many of them false positives or unreachable in practice. AI-driven SAST understands the code's intent and data flow well enough to distinguish an exploitable path from a pattern match, explain the finding in plain terms, and propose the correct fix. In an agentic program the fix is also raised and verified, not only proposed.

What is software composition analysis (SCA)?

Software composition analysis (SCA) identifies the open-source and third-party components in an application, their versions, their known vulnerabilities and their licenses. Black Duck's 2025 analysis of 965 commercial codebases found 86% contained vulnerable open-source components and 81% contained high- or critical-risk ones. SCA is necessary and produces more findings than any team can act on; the value is in knowing which components are actually loaded, reachable and exposed.

What is software supply chain security?

Software supply chain security protects the path by which code reaches production: the open-source dependencies, build pipelines, package registries, container images and third-party components an application relies on. Verizon's 2025 Data Breach Investigations Report found third-party involvement in breaches doubled to 30%. A software bill of materials (SBOM), and increasingly an AI bill of materials (AIBOM), is the inventory on which supply chain security depends.

What is runtime security?

Runtime security observes and protects applications while they run: which processes, containers and services are actually executing, what they load and connect to, and whether their behaviour departs from what is expected. Runtime context is what turns a list of theoretical vulnerabilities into a short list of real ones, because a vulnerable library that is never loaded is not the exposure a running, internet-facing one is.

What is code security, and how is a code vulnerability different from a finding?

Code security is the practice of preventing and removing exploitable weaknesses in an application's own source code: injection, broken authentication, insecure deserialization, hard-coded secrets and the rest. A finding is what a tool reports; a code vulnerability is a weakness that can actually be reached and exploited in the deployed application. Most application security programs drown in findings while the small number of true vulnerabilities go unaddressed.

What is agentic vulnerability remediation?

Agentic vulnerability remediation is the use of AI agents to close vulnerabilities rather than only report them: the agent prepares the code change, dependency upgrade, configuration fix or patch, raises it through the organization's pipelines and change control, obtains a named human approval, and verifies the vulnerability is closed after deployment. It addresses the bottleneck that has defeated most programs, which is not detection but the engineering capacity to fix.

What is Application Security Posture Management (ASPM)?

Application Security Posture Management (ASPM) is the discipline, and a category of tool, that correlates findings from many application security tools into one view, adds context, and manages the program's posture and workflow. Gartner predicted that more than 40% of organizations developing proprietary applications would adopt ASPM by 2026. ASPM answers what the posture is; an agentic platform also changes it, by carrying the fix.

How is an agentic application security platform different from ASPM and from scanners?

Scanners find; ASPM correlates and ranks; an agentic platform finds, qualifies, fixes and verifies. The defining differences are that the agentic platform holds one native picture across every layer rather than importing findings from separate tools, qualifies each finding against the business process and portfolio dependency it sits under as well as reachability and exploitation, and carries the remediation through the customer's change control under human approval.

How does Axiarete secure customer code and data?

Axiarete is SOC 2 Type II, ISO 27001 and ISO 42001 certified and HIPAA compliant. Each customer runs in a dedicated tenant, no customer code or data is used in model training, every output is explainable and auditable, and a named person approves every change that touches the estate.

How do we start with Axiarete?

Begin with the exposure that carries the most business risk: the internet-facing systems under revenue-carrying processes, including the ones in no inventory. Axiarete builds the picture of the estate, qualifies what it finds, and scopes a first nano sprint in writing that eliminates one class of vulnerability with outcomes and duration fixed. The first verified remediation is delivered within the first weeks of delivery. Request an executive briefing at info@axiarete.ai.

Begin with the exposurethat would become the breach.

Not the highest severity score, and not the longest list. Every estate has a small number of reachable, exposed vulnerabilities sitting under processes the business cannot do without, several of them in systems no inventory records. They are where an application security program should begin, because closing them changes the risk on day one and shows what the rest of the estate will yield.

Schedule a Conversation Explore the platform

What a first conversation covers

  • Where the reachable, exposed vulnerabilities in your estate are likely to concentrate, and what the picture shows within two weeks
  • How a first nano sprint is scoped in writing, with the class of exposure, SLAs, outcomes and duration fixed
  • The security package: SOC 2 Type II, ISO 27001, ISO 42001, tenancy and code handling
  • What the first quarter's verified remediations typically look like for an estate of your size