Stop AI software risk before it starts

Ship secure, high-quality code at every commit – no matter who (or what) wrote it.

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AI Software Governance

Adopt AI-driven development with confidence

Visibility into shadow AI. Audit-ready traceability for every commit — human or agent. Adaptive learning that turns every finding into stronger secure-coding capability. SCW is the AI Software Governance platform built for the agentic era.

Operationalize AI governance across software development.

Enable AI-assisted development while maintaining security oversight. Gain visibility into AI usage, apply governance workflows at commit, and align development practices with enterprise risk thresholds.

Securely scale AI software development

  • Gain enterprise-wide visibility into AI-assisted development
  • Strengthen secure coding capability across engineering teams
  • Train developers to safely review AI-generated code
AI Governance
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Prevent AI-introduced vulnerabilities at commit.

Make AI usage visible, apply secure coding guardrails at commit, and align AI-assisted development with security standards to prevent vulnerabilities across human and AI-generated code.

Reduce introduced vulnerabilities by 53%+

  • Build secure coding capability across development teams
  • Deliver policy-aligned guidance directly in developer tools
  • See how AI-generated code impacts software risk
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Scale AI development without slowing delivery.

Make AI-assisted development secure and measurable — reducing rework, avoiding security review bottlenecks, and enabling teams to ship faster with confidence.

Reduce MTTR by up to 82%

  • Improve developer security skills with adaptive learning
  • Deliver real-time guidance inside developer tools
  • Fix vulnerabilities earlier to reduce cost of rework
Engineering
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Why we’re awesome

Secure and built for the tools you already use

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*In progress
Total interactive learning activities
11k+
Vulnerability topics & security concepts
650+
AI / LLM focused learning activities
800+
Coding languages and frameworks
75+

Our latest content

Blog
February 12, 2020
The most dangerous software errors of 2019: More evidence of history repeating

Towards the end of last year, the amazing community at MITRE published their list of the CWE Top 25 Most Dangerous Software Errors that affected the world in 2019. And most of it was no surprise.

Blog
January 28, 2020
The growth spurt: Happy 5th birthday, Secure Code Warrior

I could have started this article with all the facts and figures indicating a thriving, hyper-growth startup; they are undeniably impressive and our ongoing company trajectory is strong. However, for me, these numbers don't reflect what I am most proud of in 2019.

Blog
January 1, 2020
Why DevOps Implementation is Often Unsuccessful (and How You Can Fix It)

Few companies are truly successful in their DevOps implementation. However, the right support, nurturing and understanding across the business can transform your process.

Blog
December 2, 2019
The new NIST guidelines: Why customized training is essential to create secure software

The National Institute of Standards & Technology (NIST) released an updated white paper, detailing several action plans for reducing software vulnerabilities and cyber risk.

Blog
November 21, 2019
OWASP AppSec Day 2019: Nurturing Secure Developers

These developer-focused events are among my favorite on the calendar; they provide a humbling reminder of the community that works tirelessly to educate and empower software engineers and specialists to champion security in their work.

Blog
October 31, 2019
Static Vs. Dynamic Cybersecurity Training: Impulsive Compliance, Future Problems

While regulatory initiatives will undoubtedly improve and grow over time, if organizations are already hitting the panic button and leaping into training now, they might just find themselves ill-equipped for the future.

Blog
October 16, 2019
It takes a village: How community spirit creates more secure developers

There are developers of all types, from all walks of life, and there has always been a sense of community in everything we do.

Blog
September 30, 2019
In-depth security training is raising questions in education

While secure coding needs to become a mandatory component of software engineering at the tertiary level, some universities are leading the charge in providing top-notch training and prioritizing security as part of the development process from the very beginning.p

Blog
September 24, 2019
Women in Security: Spotlight on Fatemah Beydoun

Our VP of Customer Success, Fatemah Beydoun, recently presented her talk, "Mentoring for the future: How we can all do better in fostering female cybersecurity talent" to a very receptive audience. She has been an integral part of driving positive change within the cybersecurity industry.

Blog
September 20, 2019
Coders Conquer Security: Share & Learn Series - Insecure Deserialization

Insecure deserialization can happen whenever an application treats data being deserialized as trusted. If a user is able to modify the newly reconstructed data, they can perform all kinds of malicious activities such as code injections, denial of service attacks or elevating their privileges.

Observability

Make AI-driven development risk visible

See how AI coding is used, the risk it creates, and the behavior behind it—so you can stop vulnerabilities before they ship.

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"The security champion network has been seen as a key control of that program. For one team the impact felt was enormous - with an 82% reduction in mean time to fix a vulnerability."

Mads Howard
People-Centered Security Lead at Sage

Discover shadow AI

See which AI tools, LLMs and MCPs are being used across your teams.

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Correlate true risk

Connect AI-assisted code with developer skill and introduced vulnerabilities at commit.

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Trace AI tool usage

Understand where AI-assisted development occurs—by repository, project, and contributor.

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distribution chart

Prioritize risk signals

Highlight the most urgent commit-level risk hotspots across teams and repositories.

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Learning

Reduce vulnerabilities at the source

Hands-on secure coding and AI security learning delivered in real-world developer workflows — helping organizations reduce vulnerabilities by 53%+.

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Read Case study

“Our partnership with Secure Code Warrior has been smooth and productive. They helped us implement and improve our training program, resulting in measurable risk reduction and a stronger culture of secure development.”

Sebastiaan Rijnbout
Product Owner of Development Services 
at Kamer van Koophandel

Gamified hands-on learning

Interactive play modes – including Labs, Quests, Missions, and Tournaments – build secure coding habits.

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Secure AI code development

Over 800 AI, LLM, and MCP activities teach developers to validate AI-generated code safely and efficiently.

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Empower teams to optimize

Embed a security mindset into your development process with learning beyond developer training.

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Benchmark your security program

Understand how your program compares to peers and define standards aligned to your risk strategy.

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Governance

Scale AI-driven development with confidence

Gain visibility into how AI contributes to your code, connect activity to real risk, and align development to enterprise standards — so you can reduce risk and prove trust before code reaches production.

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“Secure Code Warrior has helped us increase developer productivity, accelerate our ability to bring products and improvements to market, and significantly reduce costs and risk over time.”

Alan Osborne

Chief Information Security Officer at Paysafe

Govern AI coding policies

Bring governance visibility to AI-assisted development and help teams consistently meet secure coding standards.

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Set AI usage policies

Restrict usage to authorized AI tools, LLMs, and coding agents at the point of commit.

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Flag risk signals

Highlight AI usage and policy misalignment to support secure development decisions.

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Commit policy

Trigger policy remediation

Assign targeted adaptive learning when risky behavior or unauthorized AI use is detected.

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Govern AI-driven development before it ships

See developer risk, enforce policy, and prevent vulnerabilities across your software development lifecycle.

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AI software governance FAQs

Understand AI software governance and how to reduce AI-driven software risk

Learn what AI software governance is, why it matters, and how Secure Code Warrior helps organizations safely adopt AI-assisted development.

What is AI software governance?

AI software governance is the ability to see, measure, control, and enforce how artificial intelligence is used in software development. It includes visibility into AI coding assistants and LLMs, commit-level risk analysis, policy enforcement, and preventing risky AI-generated code from reaching production.

Why is AI software governance important?

As organizations move from developers casually using AI chatbots to AI agents autonomously generating and modifying code, the risk surface expands dramatically. These tools can introduce vulnerabilities, insecure patterns, and compliance exposure at machine speed.

AI software governance enables organizations to adopt AI safely by making AI usage visible, enforcing policy controls, and preventing AI-introduced risk before code reaches production.

How is AI development governance different from DevSecOps?

DevSecOps integrates security testing into CI/CD pipelines to detect vulnerabilities. AI development governance goes further by making AI usage visible, correlating AI-assisted commits with developer skill, enforcing AI model policies at commit, and improving secure coding behavior. DevSecOps detects risk; AI governance prevents it.

How does Secure Code Warrior reduce AI software risk?

Securing AI-generated code requires visibility into AI tool usage, commit-level risk analysis, and governance oversight across development workflows. Secure Code Warrior provides AI observability, vulnerability correlation, and developer capability insights within a unified AI software governance platform.

How do you prove AI risk reduction to leadership or auditors?

Secure Code Warrior provides enterprise dashboards, AI model traceability, and governance reporting that demonstrate measurable reductions in introduced vulnerabilities, improved developer Trust Score®™ metrics, and policy compliance across teams.

The platform also maintains audit-ready traceability of who — or what — generated specific code, including developers, AI coding assistants, LLMs, and autonomous agents. This creates verifiable AI software supply chain accountability for leadership, regulators, and auditors.

Still have questions?

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