Every penetration testing firm is facing the same pressure right now. AI tools are faster, cheaper, andincreasingly capable, and testers are using them whether the company has a policy on it or not.

There’s ahigh change AI has already entered your workflow the question is whether it has entered on your terms oryour employee’s personal Claude account.And in this industry, that distinction really matters.

The Cloud AI Problem No One Wants to Talk About

When a developer pastes code into ChatGPT, the worst case is a licensing headache. When a penetration tester does the same thing with a client’s findings, you’ve just uploaded a detailed map of a company’s vulnerabilities to a third-party cloud infrastructure you have no control over.

Besides a policy violation, that’s a potential breach of client confidentiality, NDA, and in regulated industries, compliance frameworks like GDPR or HIPAA.

The major AI providers (OpenAI, Anthropic, Google) are excellent products. But their cloud-hosted models were not designed with the data sensitivity of offensive security work in mind.

Client scope documents, discovered vulnerabilities, network diagrams, hardcoded credentials found during testing. None of that should be leaving your infrastructure, and none of it should be in a training pipeline you didn’t consent to.

The truth is that if your firm doesn’t give testers a sanctioned AI workflow, they will build their own. And it’s not likely they’ll be thinking about your client contracts when they do.

The Right Architecture Exists

The answer isn’t to ban AI. That ship has sailed, and the firms that try will just end up with testers using it covertly while competitors who embrace it properly pull ahead on speed and output quality.

The answer is to bring AI in-house, on infrastructure you control, with client data that never leaves your network.

Self-hosted AI models have matured significantly. Running a capable model locally is no longer just a research project, but an operational choice.

And when you combine a self-hosted model with an orchestration layer built specifically for security workflows, you get the productivity benefits of AI without handing your clients’ attack surface to a third party.

AI specifically designed for cybersecurity companies

PentestPad is a pentest reporting tool that reduces the time security teams spend turning raw notes into a client-ready report, while keeping the project organised around it.

The teams using it are not all in the same business. Some deliver security testing to clients. Some test their own systems in-house.

Others coordinate several external providers at once, and use the platform to keep the findings in one place.

Day to day that means project management, collaboration, retesting and report generation. Much of the tooling that usually surrounds a pentest sits inside it as well: notes, evidence and attachments, comments on findings, proposals and scope import.

Less of the work needs a scratch file, a shared drive or a spreadsheet.

Almost none of it is fixed. Reports generate from your own template rather than a generic one, the client portal carries your branding on your own domain, and the fields, layouts and statuses behind a finding are defined by your team rather than inherited.

The instructions the AI assistant writes to are yours as well, so a draft comes back in your methodology and your wording rather than a generic house style.

The same holds for where it all runs. PentestPad is available as a managed cloud service or fully self-hosted on your own infrastructure, including air-gapped, and the writing assistant can be pointed at a self-hosted model inside your own network rather than a vendor’s.

That last choice is the one pentest teams get stuck on. A finding is a client’s unremediated vulnerability, and handing it to OpenAI or Anthropic’s API sends it to a company your client never agreed to.

Most client contracts list which outside companies are allowed to handle their data, and a model vendor is not on that list.

Adding one means telling every client and usually asking them to sign off, while the data sits somewhere you did not choose for as long as someone else decides. Running the model yourself removes the question instead of answering it.

The platform exposes itself over MCP, so an agent can work against your real findings, fields and templates instead of guessing at them.

Built for agents as well as people

PentestPad is built to be driven by software as well as by a person at a keyboard, and the model doing the driving can sit inside your own network.

That is the whole answer to the problem above: the assistant is pointed at a self-hosted LLM, and client content never crosses your perimeter.

The writing assistant works from what a tester already has. Hand it scanner output, a Burp finding, a screenshot or a log file, attach the evidence, and it returns a structured finding written to the instructions your organisation has defined, so the draft arrives in your format rather than a generic one.

Underneath, PentestPad exposes itself over MCP. Methodology, past findings, templates, finding fields and the rules for writing them live in the platform, and the MCP server exposes fourteen typed tools over them, from searching projects and findings to filing a new one from a template, updating remediation after a retest, or adding a comment.

The platform stays the source of truth and the agent holds no state of its own.

Run end to end the stack is three parts, all on hardware you control. PentestPad is the knowledge base, a local model does the reasoning, and a terminal harness is wired to both.

PentestPad’s own team uses Qwen3 Coder through Ollama, with OpenCode or Claude Code as the harness.

For teams that would rather not assemble one, there is a command-line agent for macOS, Linux and Windows, carrying six customisable specialists across web, network, reconnaissance, API and mobile testing, plus a general one for methodology and tool selection.

How the report gets built

A project holds the client, the assessment type, the scope, the testers assigned to it and the timeline.

Findings attach to it as testing progresses, so what is in scope, who is working on it and what has been found so far sit together rather than across a folder, a chat thread and a spreadsheet.

Each finding carries a title and description, the affected assets, severity, remediation, references and the supporting evidence.

Severity is set with a built-in CVSS calculator, and where a team hides its own impact and probability fields the risk rating derives from the CVSS score instead.

Findings do not have to start empty. A library of reusable vulnerability templates sits alongside the projects, searchable by name and filterable by assessment domain, and importing one fills every field of a new finding with your own house description, remediation text and CVSS vector, leaving only the engagement-specific detail to write. Executive summaries work the same way.

Findings move through statuses your team defines, from draft to ready. Comments attach to individual vulnerabilities rather than to the document, and revision history shows what changed between drafts.

The report itself is built from your own file, with placeholders dropped in where the data belongs, and the PentestPad team does the conversion at no cost. For teams starting from scratch there is a free penetration test report template to work from.

Generation pulls the structured data through it. Tables of contents regenerate on every build, charts and tables populate from the findings, and cross-references resolve through a dynamic link system so they stay correct when content moves.

Reusable field templates cover report-level and finding fields, and a live preview renders the document in the browser before anything is exported.

What comes out covers executive summary, scope, methodology, findings, technical detail, remediation recommendations and supporting information.

A single project can span more than one assessment domain, with each finding tagged to the domain it came from, so a web application test and a network test for the same client arrive as one report with the findings grouped rather than as two separate deliverables.

A library of template functions ships with the platform, from parsing a CVSS vector and deriving a risk rating to counting findings by severity or filtering scope down to just the IPs or just the URLs.

You can define your own JavaScript functions and call them from the template. Reports generate over the API, so a pipeline can produce one without a human opening the platform, and a finished PDF can be encrypted with a password you supply.

Individual DOCX or PDF files can be swapped inside an existing report without rebuilding it.

Branding, access and retention

Whitelabeling covers the logo, the colours and the domain, so someone logging in to check progress arrives at your brand rather than the vendor’s, down to the 2FA challenge screen, and exported reports carry the same identity.

Access control is granular rather than role-shaped. Pentester, Manager and Admin ship as defaults, but you can define your own roles from a permission set covering projects, findings, reports and clients, assign more than one role to a single user, and override individual permissions on top of a role where it does not quite fit.

Role administration is itself a separate permission, so team administration can be granted without also handing over the ability to edit roles. Client accounts are created and invited over the API, and client API keys are restricted separately from your team’s.

Uploads are scanned for malware and flagged files rejected, though anyone with the permission can override that and upload a known sample anyway. Scanning is always on for the managed service and optional when self-hosted.

The data lifecycle is configurable in the same way. Inactive projects archive automatically, and archived reports can be deleted on a schedule you set rather than accumulating until someone remembers them.

Deployment, compliance and pricing

Area	Detail
Deployment	Managed EU cloud, or fully self-hosted including air-gapped, on every plan
AI	Hosted, or pointed at a self-hosted LLM in your own network
Agent tooling	MCP server, plus a CLI agent for macOS, Linux and Windows
Compliance	EU-based entity, GDPR, ISO 27001 certified
Export	DOCX, PDF, XLSX and API
Integrations	Two-way Jira sync, imports from Burp Suite, Nessus, Qualys, Nuclei, OpenVAS, CSV and JSON, REST API, MCP
Pricing	Professional EUR 49, Business EUR 129, per pentester per month; Enterprise on request

Self-hosting is available on every tier, which matters when a client contract or an internal policy restricts where report data may live.

Self-hosted instances check a version endpoint and raise update notifications, so an isolated deployment knows when it has fallen behind.

Project data, evidence, the finding library, penetration test report template and user configuration export in DOCX, PDF, XLSX or over the API.

Quotes

Available if useful. Use either, both or neither.

“Where a client’s findings are allowed to live is decided by the team holding them, and for many that means nowhere outside their own infrastructure. That is the requirement we built the AI around, so the model runs wherever a team needs it to, including entirely inside their own network.”

Luka Šikić, CEO, PentestPad, Secure Block.

“Most teams reshape the fields, the layout and the statuses to match how they already work, set which parts a client can see, put their own branding on the portal and write their own instructions for how the AI should fill a finding in. That was the point of building it that way.”

Mirna Novak, Director, PentestPad

The post PentestPad: How Pentest Companies Adapt In The Era of AI appeared first on Cyber Security News.

Dhananjay Ganjoo, Managing Director – India & SAARC 

The uncomfortable part of an adaptive attack is not how quickly it starts, but  how quickly it can change course.  

AI-assisted operations can probe environments, learn from responses, switch techniques and chain subsequent actions while an attack is still in progress.

Anthropic’s 2026 analysis of 832 accounts banned for malicious cyber activity points to this shift.

While much of the activity it observed focused on preparing for attacks, the highest-risk actors used AI in live operations, including autonomous execution, orchestration and real-time pivot decisions.  

For defenders, this creates a moving target. The attack that enters an environment may not follow the same pattern as it progresses through it. 

Applications present a moving target of their own. They span on-premises infrastructure, multicloud environments, Kubernetes clusters and the edge, with APIs carrying traffic between users, workloads and services.

Endpoints appear, integrations change and application behaviour evolves continuously.  

Preventive controls and known-threat detection remain essential. But when both the threat and environment can change in real-time, security also needs to understand  what applications and APIs are doing while they are running.  

When the attack pattern keeps changing 

Application security has become very good at recognising known bad behaviour. Signatures identify established techniques. WAF policies inspect requests against defined rules.

API schemas establish how endpoints are expected to be used. Threat intelligence adds knowledge of emerging campaigns and indicators. 

The challenge begins when malicious activity does not stay inside those familiar patterns. 

An attacker probing an API may alter request structures after an unsuccessful attempt, move to another endpoint, change the sequence of calls or abuse legitimate application functionality based on what the environment reveals.  

That means defenders need another layer of context; how the attacker behaves as it develops. 

A single request may reveal very little. But look at the sequence around it. Which endpoints are being called? How are request patterns changing? Which resources are being accessed? Is activity moving outside established patterns? A very different picture can emerge. 

Industry Research found that 48% of organisations update production APIs daily or more frequently, yet only 19% maintain a fully automated and continuously updated API inventory.

Security teams are therefore dealing with two variables at once, an application estate that changes continuously and malicious activity that may not follow a predictable path. 

Runtime is where behaviour becomes visible 

Much of what security knows is established before traffic reaches a running application, identities, policies, configurations, API definitions, vulnerability intelligence and threat indicators. 

What cannot always be known in advance is how malicious activity will behave once it encounters the application. Runtime provides that context. 

Observing live application and API traffic allows security teams to connect signals that may mean little on their own, changes in request frequency, repeated access across objects, an unexpected sequence of API calls or traffic moving between endpoints.   

This is where behavioural detection complements established security controls. Known-threat detection asks whether traffic resembles something defenders already understand.

Behavioural detection asks whether the application or API is behaving as expected? 

For threats capable of changing during execution, that distinction can make the difference between seeing isolated events and understanding what is happening across the application data path. 

Detection must lead to enforcement 

Visibility alone does not reduce risk. 

If anu unusual behaviour is identified only after the application has processed the traffic and the attacker has achieved the objective, the insight has arrived too late.

Runtime visibility therefore has to connect detection with policy enforcement capable of acting on live application and API traffic. 

The response does not have to be binary. Some malicious activity should be blocked immediately.

In other cases, security teams may rate-limit requests, restrict access to endpoint, tighten a policy or isolate suspicious activity while legitimate traffic continues. 

That distinction matters because security teams are protecting payment systems processing transactions, healthcare platforms supporting patients, e-commerce services serving customers and industrial applications supporting operations.  

Stopping an attack by unnecessarily stopping the application is not resilience. The objective is to prevent malicious activity from achieving its goal while allowing legitimate users and services to continue operating. 

Protection has to follow the application 

The challenge becomes harder when an application spans several environments. 

A customer-facing service may have workloads in a public cloud, sensitive systems on premises, containerised services running in Kubernetes and APIs connecting all of them.

Each environment may have different controls, policies and operational teams.  

Attack path does not respect those boundaries 

If visibility and enforcement change every time application traffic crosses an environment, blind spots emerge where organisations need consistency.

Protection therefore has  to follow the application and its APIs across the hybrid multicloud estate rather than depend on where workload happens to run. 

That requires a consistent view of application traffic, the ability to identify malicious or anomalous behaviour wherever it appears, and controls capable of responding without unnecessarily disrupting legitimate traffic. 

Availability is part of the security outcome 

Application security is ultimately an availability problem. Modern businesses depend on applications being continuously accessible.

When an application or API goes down, a security incident quickly becomes a business interruption. 

Industry research found that significant API, bot and DDoS-related incidents take organisations an average of 2.8 hours to fully resolve.

It also estimated the average cost of application-layer DDoS downtime at $7,530 per minute. 

For security leaders, success therefore cannot be measured simply by how much traffic is blocked or how many threats are detected.

What matters is whether the organisation can contain malicious activity while keeping critical services operating. 

Security and application delivery increasingly have to move together. Protection has to be strong enough to stop malicious traffic, precise enough to preserve legitimate traffic and consistent enough to work wherever the application runs. 

From knowing the threat to being ready for it 

Threat intelligence, vulnerability management, signatures, access controls and preventive protections remain fundamental to cyber defence.

But organisations cannot assume they will always know the exact shape of an attack before it reaches a running application. 

As threats become more adaptive, security needs to know in advance with what it can learn from application and API behaviour at runtime.

Continuous visibility must feed behavioural detection, and behavioural detection must translate into policy enforcement before malicious activity becomes operational impact. 

This is what continuous security readiness means. It is less about predicting every attack, but recognising when behaviour changes, assessing the risk and acting while the application remains available. 

Cyber resilience will increasingly be determined in the space between the first meaningful deviation and the business disruption.

The organisations best prepared will be those that can recognise that change early, adapt their protection and keep the applications their business running. 

The post When Threats Don’t Wait, Security Can’t Either  appeared first on Cyber Security News.

A website builder’s biggest security feature is invisible: everything you never have to patch. Hosted platforms took the jobs that get self-managed sites hacked — core updates, TLS renewal, server hardening — and made them the vendor’s problem, which is why the real 2027 question isn’t “builder or not” but which builder’s security program deserves your business. We ranked the best of the best — the leading mainstream platforms — purely on protection. Wix takes #1 overall; Shopify owns the commerce lane; Squarespace and Webflow complete the podium.

Key Takeaways

• #1 overall: Wix — a genuine enterprise-grade security program (bug bounty, threat response, default TLS/WAF-backed delivery) behind a consumer product.
• #1 for selling online: Shopify — PCI DSS Level 1 by default; checkout security you could not affordably build yourself.
• The builder covers the platform — you still own the account: most builder-site “hacks” in 2027 are stolen logins and rogue apps, not server breaches. Multi-factor authentication and app hygiene are your half of the contract.
• Check the certificates, not the adjectives: ISO 27001/SOC 2-class attestations and a public security page separate programs from promises. [VERIFY]

How We Scored (Methodology)

Research-based evaluation of the market-leading builders on: platform security program (certifications, bug bounty, disclosure process), secure-by-default posture (TLS, WAF/DDoS-backed delivery, backups/versioning), account protections (2FA methods, roles, session controls), ecosystem risk (app/plugin vetting), and track record. No lab testing; no paid placement; editorial scores are excluded from structured data, and fast-moving certification claims carry [VERIFY].

The 2027 Protected-Builder Power Rankings

#	Builder	Award	Score*
1	Wix	Best-protected overall	9.0
2	Shopify	Best-protected commerce	9.0
3	Squarespace	Best secure simplicity	8.6
4	Webflow	Best for design teams w/ compliance needs	8.5
5	Duda	Best for agencies at scale	8.3
6	WordPress.com	Best managed route to WordPress	8.1
7	Hostinger Builder	Best budget with security floor	7.8
8	GoDaddy Websites	Best bundled-everything entry	7.6

*Editorial research-based scores, not lab results.

#1 Wix — Best-Protected Overall

Snapshot: Free–premium tiers | Default TLS, platform WAF/DDoS absorption, 2FA, roles | Bug bounty + ISO/SOC-class attestations.

Wix runs security like the software company it is: a public program with certifications (ISO 27001/27701-class, SOC 2-class, PCI for its commerce lane), a bug bounty, automatic TLS on every site, and web application firewall-class threat detection absorbed at platform scale — none of which the site owner ever configures.

Add granular team roles and multiple 2FA methods, and the gap between “my cousin’s Wix site” and an enterprise-hosted page is smaller than the price suggests.

Bottom line: the strongest all-round security program in the mainstream lane.

#2 Shopify — Best-Protected Commerce

Snapshot: Commerce tiers | PCI DSS Level 1 across the platform | Fraud analysis, Shop Pay | Bug bounty veteran

If the site takes payments, Shopify’s case is close to unanswerable: the whole platform operates at PCI DSS Level 1, checkout and card handling never become your engineering problem, fraud analysis ships in the box, and its long-running bug-bounty program is among the industry’s most active. The residual risks are yours to manage — staff logins (enforce 2FA) and third-party apps (vet scopes) — because attackers go where the money is.

Bottom line: the safest way for a non-security team to run a store in 2027.

#3 Squarespace — Best Secure Simplicity

Snapshot: Flat tiers | Auto-TLS, managed everything, 2FA | Closed ecosystem = small attack surface

Squarespace’s security story is its architecture: a tightly closed platform with no plugin jungle, automatic TLS and infrastructure wholly managed, 2FA and session controls on accounts — fewer moving parts than any rival here, and fewer things to misconfigure. The trade is flexibility; the reward is that the attack surface stays almost entirely Squarespace’s problem. [VERIFY]

Bottom line: minimal surface, minimal user error — simplicity as a security control.

#4 Webflow — Best for Design Teams With Compliance Needs

Snapshot: Site/workspace tiers | SOC 2-class attestation, auto-TLS, SSO on higher tiers | Enterprise lane with WAF/DDoS depth [VERIFY]

Webflow pairs designer power with grown-up assurance: published compliance attestations, default TLS and hosted delivery on major cloud/CDN infrastructure, page-level publishing controls, and an enterprise tier (SSO, advanced DDoS/WAF posture) that procurement teams can take seriously. For agencies and product teams who must answer a security questionnaire — or commission web application penetration testing against a client build — Webflow is the builder that has the paperwork. [VERIFY]

Bottom line: creative control with compliance answers attached.

#5 Duda — Best for Agencies Running Many Sites

Snapshot: Agency tiers | ISO 27001-class certification, auto-TLS fleet-wide | Client roles + audit-friendly ops [VERIFY]

Duda sells to the people responsible for hundreds of small-business sites, and its security posture matches: certification-backed platform, automatic TLS across the fleet, granular client/team permissions, and centralized control that keeps one weak client login from becoming a portfolio incident. For the agency lane, per-site security multiplied by scale is the product.

Bottom line: fleet-grade protection for the people who manage sites in bulk.

#6 WordPress.com — Best Managed Route to WordPress

Snapshot: Free–business tiers | Automattic-managed core/updates, auto-TLS, 2FA | Plugin access only on higher tiers

The security difference between WordPress.com and self-hosted WordPress is the whole point: Automattic patches core, runs the infrastructure, and keeps TLS and backups automatic — removing the unpatched-plugin pathway that makes self-hosted WordPress the internet’s most-attacked CMS. Open plugin access on business tiers reopens ecosystem risk deliberately; treat every plugin as a vendor decision. [VERIFY]

Bottom line: WordPress flexibility with the dangerous jobs outsourced.

#7 Hostinger Builder — Best Budget With a Real Security Floor

Snapshot: Value tiers | Auto-TLS, platform-managed hosting, 2FA on accounts | CDN/WAF-backed delivery [VERIFY]

Hostinger’s AI-era builder brings the essentials — automatic TLS, managed infrastructure, account 2FA, CDN-fronted delivery — at prices that make “secure enough, honestly cheap” a fair summary. The program depth (bounties, published attestations) trails the leaders, which is what separates a floor from a flagship; for a portfolio site or small venture, the floor is real. [VERIFY]

Bottom line: the budget pick that still clears the security bar.

#8 GoDaddy Websites — Best Bundled-Everything Entry

Snapshot: Bundle tiers | Auto-TLS, managed platform, one-vendor stack | Upsell-heavy security add-ons [VERIFY]

GoDaddy’s builder delivers the managed-platform basics — TLS, hosting, backups handled — inside the domain-email-site bundle its audience buys for one-invoice simplicity. Navigate the add-on catalog with care: some “security extras” duplicate what the platform (or this list’s rivals) include by default. [VERIFY]

Bottom line: fine protection for the set-and-forget site; read the add-ons skeptically.

Full Comparison Table

Builder	Default TLS	Platform WAF/DDoS	2FA	Certifications/program	Best for
Wix	Yes	Yes (absorbed)	Multiple methods	ISO/SOC-class + bounty [VERIFY]	Overall protection
Shopify	Yes	Yes	Yes (enforceable)	PCI L1 + bounty	Commerce
Squarespace	Yes	Yes	Yes	Closed-platform posture [VERIFY]	Simplicity
Webflow	Yes	Yes (ent. depth)	Yes + SSO (tiers)	SOC 2-class [VERIFY]	Compliance-needing teams
Duda	Yes	Yes	Yes	ISO-class [VERIFY]	Agencies/fleets
WordPress.com	Yes	Yes	Yes	Automattic program	Managed WordPress
Hostinger	Yes	Yes (CDN-backed)	Yes	Floor-level [VERIFY]	Budget
GoDaddy	Yes	Partial/add-on [VERIFY]	Yes	Bundle posture	One-vendor entry

Yes/No Capability Table

Builder	Automatic TLS on every site?	Two-factor authentication?	Team roles/permissions?	Public bug bounty program?	PCI-covered checkout built in?
Wix	Yes	Yes	Yes	Yes [VERIFY]	Yes (commerce plans)
Shopify	Yes	Yes	Yes	Yes	Yes (Level 1)
Squarespace	Yes	Yes	Yes (contributor roles)	Partial [VERIFY]	Yes (via integrated payments)
Webflow	Yes	Yes	Yes (workspaces)	Partial [VERIFY]	Via integrations
Duda	Yes	Yes	Yes (client/team)	Partial [VERIFY]	Via integrations
WordPress.com	Yes	Yes	Yes	Yes (via Automattic/HackerOne) [VERIFY]	Via plugins/integrations
Hostinger	Yes	Yes	Partial	No [VERIFY]	Via integrations
GoDaddy	Yes	Yes	Partial	Partial [VERIFY]	Yes (commerce tiers)

Your Half of the Contract: Five Habits That Keep Any Builder Safe

The platforms above patch the servers; the 2027 breach reports say the rest is on you. Turn on 2FA for every account with editor access — stolen logins, not hacked servers, are how builder sites deface and redirect, and a password manager plus anti-phishing awareness closes most of that door. Audit third-party apps and plugins quarterly (Shopify apps, WordPress.com plugins, embedded widgets): every one is a vendor with your visitors’ trust, and an occasional pass with a website security scanner catches what the quarterly review misses. Prune old contributor accounts the day people leave. Keep your domain registrar locked and 2FA’d — DNS hijacking beats any platform’s security — and consider dark web monitoring for leaked admin credentials if the site is your business. And verify the recovery path before you need it: know what the platform’s backups/versioning actually restore, and export your content on a schedule anyway.

FAQs

What is the most secure website builder in 2027? Wix leads overall on program depth (certifications, bounty, default protections), Shopify leads wherever payments happen, and Squarespace’s closed simplicity makes it the hardest to misconfigure. All eight here clear a bar self-managed sites rarely do.

Are website builders safer than self-hosted WordPress? For most owners, yes — the platform patches core, TLS, and infrastructure automatically, removing the unpatched-plugin pathway behind most CMS compromises. Self-hosting wins only when you staff the maintenance it demands.

Can a Wix or Squarespace site still get hacked? The platform rarely; your account, sometimes. Phished logins, weak passwords without 2FA, rogue third-party apps, and hijacked domains cause most real-world incidents — all preventable with the habits above.

Do builders include DDoS protection? The leaders absorb attack traffic at platform scale as a matter of architecture — you’re sharing enterprise-grade infrastructure comparable to standalone DDoS protection services. Depth varies by tier (Webflow’s enterprise lane, for example), so high-risk sites should confirm specifics.

Which builder is safest for an online store? Shopify, by architecture: PCI DSS Level 1 across the platform and checkout handled entirely by the vendor. Enforce staff 2FA and vet apps — that’s the half attackers actually test.

Verdict

The best-protected builder is the one whose security program you never have to think about: Wix for the strongest all-round posture, Shopify when money moves, Squarespace when simplicity should shrink the attack surface, Webflow when procurement wants paperwork, Duda when you guard a fleet, WordPress.com when you want WordPress without its chores, Hostinger and GoDaddy when budgets lead — then hold up your half: 2FA everywhere, apps audited, domain locked.

Read next on Cybersecurity News:

• Top 10 Best Web Application Firewall (WAF) in 2026
• Best DDoS Protection Tools & Services
• 10 Best Web Scanners for Website Security
• Top 10 Best Password Managers
• Top 10 Best Multi-Factor Authentication (MFA) Solutions in 2026
• Top 10 Best Passwordless Authentication Solutions in 2026
• 10 Best Anti-Phishing Tools in 2026
• 10 Best Dark Web Monitoring Tools in 2026
• Top 10 Best Web Application Penetration Testing Companies in 2026
• 10 Best Vulnerability Assessment and Penetration Testing (VAPT) Tools in 2026

The post The Best Protected Website Builder in 2027: Which Platform Keeps Your Site Truly Safe [Ranked & Scored] appeared first on Cyber Security News.

Adam Ochayon, VP of Strategy, Oasis Security 

Deploying agentic AI in the enterprise is no longer optional – it’s fundamental to survival. And the main unlock to ensure security while deploying agentic AI is through agentic access management. 

AI agents improve efficiency, reduce costs, and automate both complex and repetitive tasks: From HR and marketing to IT and finance, every part of an organization can benefit from agentic AI.

Our Fortune 500 customer data showed AI agent adoption up 840× year-over-year in 2025, underscoring the velocity at which forward-leaning companies are deploying agentic AI.  

Enterprise survival hinges on evolving your technology stack to adopt AI rapidly, but challenges persist. Non-Human Identities (NHIs) now outnumber human identities by up to 144:1. 

Many organizations deploy AI agents without an access management platform purpose-built for agentic AI, or the infrastructure to govern or secure NHIs.   

As a business leader, how should you radically adopt AI while maintaining complete control? 

What Happens When Access Control Fails (or Doesn’t Exist) 

To get the most out of your AI agents, they need access. Agents without access have no agency and are essentially useless – but agents with unfettered access are incredibly powerful and dangerous. 

An agent’s mission is simple: Succeed at the task it’s given by its human user. That drive is powerful and dangerous at machine speed, as agents lack the boundaries human users operate by: they are designed to execute. 

We’ve seen what happens when access control fails and why an agentic access management platform is critical.

In one case, a Cursor AI coding agent powered by Anthropic’s Claude deleted Pocket OS’s entire production database including all backups in just nine seconds. 

The agent independently found an overprivileged token, inferred a fix, and executed a destructive command. No attacker or malice caused this business disruption – just a goal-seeking agent with too much access. 

A separate vulnerability disclosed in Claude Desktop also showed how little it can take to trigger that kind of failure.

A single crafted link was enough to bypass the user’s review step entirely, letting an attacker exfiltrate conversation history or run code on the victim’s machine, all without the user knowing they’d clicked on anything unusual.

Anthropic fixed the issue once notified, but the exposure made the point clear that an agent, given access, will act on whatever instruction reaches it, and it can’t tell a legitimate one from a malicious one on its own.  

This is what happens when legacy permissions models meet agentic AI. Most enterprises are still managing access in broad terms as coarse roles, where an identity either has access to a system or it doesn’t.

Agents then inherit that same sweeping access – but unlike a person, they can act on it at a scale and speed allowing them to take full advantage. The gap between theoretically overprivileged to risk and business disruption has collapsed. 

[Text Wrapping Break]The answer isn’t blocking agents. It isn’t giving them the keys to everything either. 

It’s applying controls allowing them to act based on intent, at machine speed, but governed by policy – without the ability to touch what they shouldn’t.[Text Wrapping Break] 

Least Privilege is Dead  

Security teams have relied on least privilege for years, trying to give identities only the access they need and nothing more.

That model assumes the identity behaves predictably. A script runs the same way every time. A workload does what it’s programmed to do. 

However, agents don’t work that way. They reason and explore. And when given a goal, an agent can find its own path to it, non-deterministically, in ways its designers didn’t explicitly plan for. 

That’s what makes agents powerful, and it’s exactly why least privilege breaks down as a control model. 

What enterprises need instead is least agency, which gives an agent access to only what it needs to complete the specific task in front of it, not standing access to everything it might theoretically touch.

This way it’s a narrower, more dynamic version of least privilege built for identities that can reason rather than just execute. 

The Identity Blind Spot for Enterprises 

Adopting agentic AI safely depends on the same foundations enterprises needed for workload identity, and for most organizations those foundations aren’t solid. 

Long-lived credentials and static authentication methods are still common, and they become far riskier once an agent is the one holding them. 

The more mature organizations are moving toward strongly bound, short-lived authentication. That shift takes time, and most enterprises are somewhere in the middle of that maturity curve where they’re trying to move fast on AI adoption but their underlying identity infrastructure hasn’t caught up. 

Bye-Bye to Point Solutions 

In today’s AI age, the control plane that matters is identity and access. Why? Because application-level point solutions become easier for AI itself to absorb or replicate. 

Access governance has to live at the infrastructure layer, not bolted onto individual applications. So it’s necessary to prioritize adopting technologies that will let you enter the AI era securely, and removing point solutions and disparate tools that add complexity without adding control.  

When everyone claims to do AI security, in practice almost no one is solving a specific piece of it well. The organizations that will fare best are the ones that get precise about which layer of the problem a given tool actually addresses, rather than assuming broad coverage where none exists.  

Getting the infrastructure layer right is only half the equation. The other half is who’s running it. 

Security Teams Becoming AI Governance Teams 

The skills gap in identity and access is growing quickly, and it’s one of the biggest workforce risks enterprises face right now, even if it doesn’t get talked about as much as job loss.

The global cybersecurity workforce gap now sits at roughly 4.8 million unfilled positions, and nearly 90 percent of organizations report critical shortages specifically in cloud and AI security. 

That demand is only accelerating as old systems and new AI infrastructure now have to be managed side by side. 

This is pushing security teams into a role that looks less like traditional security operations and more like AI governance. 

Sixty percent of CISOs now cite the skills gap itself, not headcount, as their top workforce concern, the first time that’s overtaken staffing shortfalls, and rapid enterprise AI deployment is the primary driver behind it.

The work isn’t only finding what’s exposed anymore. It’s understanding how a given system is accessing resources, who’s accountable for it, what risk that exposure creates, and what the organization can actually do about it. 

That shift also changes what’s valuable in a security career. People who only execute defined tasks will have less leverage than people who can design and orchestrate systems of control. Upskilling isn’t optional anymore; it’s the difference between keeping pace and falling behind.

Most IAM professionals were trained on human identity models, so building fluency in non-human identity governance means seeking out training that treats it as its own discipline rather than an extension of existing IAM knowledge. 

Get Governance Right, or Get Left Behind 

None of this works without people who understand both the systems and the stakes. Agents still execute human intent, but the scale has changed fast. 

Gartner projects that 40% of enterprise applications will be integrated with task-specific AI agents by the end of 2026, up from less than 5% in 2025. At that scale, agents must be treated not as tools, but as actors. Capable, fast, and in need of strict governance. 

Business survival requires two simultaneous imperatives: Radical adoption of AI and radical control. Give human employees the tools they need to move at the pace of ideas. 

Give agents the access they need to create value and the boundaries they need to avoid risk. 

The future belongs to organizations that are fast enough to harness AI and wise enough to contain it. 

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