Stop AI software risk before it starts
Ship secure, high-quality code at every commit – no matter who (or what) wrote it.
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
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
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
Secure and built for the tools you already use
Our latest content
A critical vulnerability, CVE-2024-3094, was discovered in the XZ Utils data compression library used by major Linux distributions, introduced through a backdoor by a threat actor. This high-severity issue allows for potential remote code execution, posing significant risks to software build processes. The flaw affects early versions (5.6.0 and 5.6.1) of XZ Utils in Fedora Rawhide, with an urgent call for organizations to implement patches. The incident underscores the critical role of community volunteers in maintaining open-source software and highlights the need for enhanced security practices and access control within the software development lifecycle.
Generative AI offers financial services companies a lot of advantages, but also a lot of potential risk. Training developers in security best practices and pairing them with AI models can help create secure code from the start.
By following secure coding practices, developers can help to protect their applications from vulnerabilities that can be exploited by attackers. Just as a well-built house is less likely to collapse, a well-coded application is less likely to be hacked.
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.
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%+.
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.
Govern AI-driven development before it ships
See developer risk, enforce policy, and prevent vulnerabilities across your software development lifecycle.
Resources to get you started
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.