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Security that helps you close the enterprise deal.

The first big customer sends a security questionnaire and asks for your SOC 2 report. You get a security program that answers both, cloud and code practices that hold up to review, and guardrails for AI coding tools, from an architect who has worked under SOC 2, ISO 27001 and FedRAMP.

  • SaaS startups and growing software companies
  • Custom software and app development shops
  • IT and managed service providers
  • Data, analytics and AI startups
  • Health tech and fintech companies
  • Companies selling to government or enterprise

What makes software company security different

Small software companies move fast, and security trails behind: shared admin accounts in the cloud console, API keys in the repository, and production access for everyone who ever needed it once.

That works until a customer asks. Enterprise buyers send questionnaires, require SOC 2 or ISO 27001, and write security terms into the contract. A credible answer shortens the sales cycle. A weak one stalls it in procurement.

AI coding assistants raise the stakes. They speed up development, and they also make it easier to leak secrets, ship code nobody reviewed, or paste customer data into a prompt.

Rules you may answer to

Few of these are laws. Your customers make them mandatory anyway.

SOC 2
An attestation by an independent CPA firm against the AICPA Trust Services Criteria. A Type I report looks at your controls at a point in time; a Type II tests them over a period, usually three to twelve months.
ISO/IEC 27001
The international standard for an information security management system, certified by an accredited body. Common with European and global customers.
FedRAMP 20x
Cloud services sold to federal agencies need FedRAMP authorization. FedRAMP 20x is the newer, automation-driven path to it.
Your customers’ rules
Selling into healthcare, finance or retail brings their rules into your product: HIPAA business associate agreements, GLBA, PCI DSS and data protection terms such as GDPR.
AI governance
Customers are starting to ask how you build and run AI features. The NIST AI Risk Management Framework and ISO/IEC 42001 are the common references.

Where software companies get hurt, and how I close the gap

Software companies get attacked through the same doors as everyone else, plus a few of their own. Here’s what the data shows and what I do about each.

  1. 28.65Mnew hardcoded secrets exposed in public GitHub commits in 2025, up 34%

    Secrets in the code

    Leaked AI service keys rose 81%, and 32.2% of internal repositories contained at least one secret. A private repo isn’t a safe place for credentials either.

    What I doSecret scanning on every commit, credentials moved into a vault, keys rotated after any exposure, and short-lived access wherever your platform supports it.

    Source: GitGuardian State of Secrets Sprawl 2026, via The Hacker News

  2. 48%of breaches involved a third party, up from 30% the year before

    Your vendors are your attack surface

    Cloud providers, SaaS tools, open-source packages and contractors all have a path into your systems, and your customers will ask how you manage them.

    What I doA vendor inventory with risk tiers, dependency scanning, least-privilege access for integrations and contractors, and documentation that answers the questionnaire.

    Source: Verizon 2026 Data Breach Investigations Report, via TechRepublic

  3. 31%of breaches began with an exploited vulnerability, the most common way in

    Unpatched systems and exposed services

    Exploitation outpaced stolen credentials, at 13%, as the way attackers first got in. Internet-facing apps, VPNs and forgotten test environments are the usual targets.

    What I doAn inventory of everything you expose, patching on a schedule tied to severity, and regular outside-in scans of your cloud and applications.

    Source: Verizon 2026 Data Breach Investigations Report, via TechRepublic

  4. 67%of users accessed AI services through non-corporate accounts on company devices

    Shadow AI on developer laptops

    Code, logs and customer data go wherever a developer’s personal AI account sends them, outside your contracts and your customers’ expectations.

    What I doApproved business-tier AI tools that are easier to use than the personal ones, a short written AI policy, and controls that make the safe path the default.

    Source: Verizon 2026 Data Breach Investigations Report, via TechRepublic

Related services: Network security & cybersecurity · Cloud, Microsoft 365 & Google Workspace · Secure AI · Agentic operations · AI consulting & integration

Where AI helps, and where it needs guardrails

AI coding tools are now part of how software gets written. The question is whether your code, secrets and customer data stay where they belong.

Good places to start

  • Code completion and refactoring with business-tier tools that don’t train on your code
  • Tests, documentation and release notes
  • Security questionnaire answers drafted from your own approved policies
  • Summarizing logs and incidents to speed up troubleshooting
  • AI features in your product with documented data handling customers can review

Keep out of AI tools unless approved

  • API keys, tokens and credentials in prompts or AI-generated config
  • Customer data in prompts or test datasets
  • AI-generated code merged without review
  • AI agents with write access to production

How a secure AI setup works

Put AI to work in your product and your operations

For software companies, AI is both a feature to ship and a tool to run the business. Both need the same thing: architecture, data handling and monitoring your customers can trust.

AI features in your product

Vision, prediction and AI agents designed into your product with the data handling and evaluation enterprise buyers ask about.

What it covers

  • Architecture for vision, prediction and agent features
  • Model and vendor selection with the data terms reviewed
  • Evaluation against known-good answers before and after release
  • Monitoring for accuracy, drift and cost in production
  • Documentation that answers the AI questions in security reviews

Best forTeams adding AI features that enterprise customers will scrutinize.

  • Faster launches
  • Fewer surprises
  • Easier security reviews

AI for cloud and engineering operations

Your logs, metrics and cloud bill watched for the problems people only notice after they’ve cost something.

What it covers

  • Anomaly detection on logs and metrics
  • Incident timelines and summaries drafted automatically
  • Cloud cost anomalies and waste flagged
  • Security alerts triaged before a person picks them up

Best forSmall teams running production without a dedicated ops group.

  • Faster recovery
  • Lower cloud bills
  • Fewer pages at 2 a.m.

How it gets set up

  • Customer data handled the way your contracts and SOC 2 controls say it is.
  • Infrastructure as code, so the AI stack is reviewable and repeatable.
  • Ongoing agentic operations: accuracy, cost and behavior monitored after launch.

AI consulting & integration · Agentic operations

Common questions

Do we need SOC 2 or ISO 27001?

Ask your customers. U.S. buyers usually ask for SOC 2; European and global customers often prefer ISO 27001. Many of the controls overlap, so building one well gets you most of the way to the other.

Can you do our SOC 2 audit?

No. SOC 2 reports are issued by independent CPA firms. I help you get ready: scoping, a gap assessment, the policies and controls, and the evidence your auditor will ask for.

How long does SOC 2 take?

Readiness work often takes a few months for a small company, depending on where you start. A Type I report can follow soon after; a Type II needs an observation period, usually three to twelve months.

Should we let developers use AI coding assistants?

Yes, with guardrails. Use business-tier tools that don’t train on your code, keep secrets out of prompts with scanning and a vault, and require review for AI-generated changes the same as any other code.

Sources

  1. GitGuardian State of Secrets Sprawl 2026, via The Hacker News
  2. Verizon 2026 Data Breach Investigations Report, via TechRepublic
  3. AICPA, SOC 2
  4. FedRAMP 20x
  5. NIST AI Risk Management Framework
  6. ISO/IEC 42001

Figures and rules on this page were checked against these sources on October 27, 2026, using the latest edition available. This page is general information, not legal advice.

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