AI
Safeguard articles tagged "AI" — guides, analysis, and best practices for software supply chain and application security.
17 articles
AI-Generated SBOMs: How Accurate Are They?
LLMs can now generate SBOMs from source code and documentation. We tested five AI SBOM generators against traditional tools to measure accuracy, completeness, and reliability.
OpenAI's Daybreak: An Honest Assessment of Codex Security, GPT-5.5-Cyber, and the Find-Validate-Patch Loop
Daybreak is the most complete attempt yet to turn a frontier model into a vulnerability-finding-and-fixing system. We break down what it gets right, where the verification and economics still bite, and how it fits alongside a purpose-built engine.
Introducing the Safeguard MCP Server: AI-Native Software Supply Chain Security
Safeguard launches its MCP Server, bringing software supply chain security directly into AI-powered development workflows through the Model Context Protocol.
Safeguard Griffin AI: Autonomous Vulnerability Remediation That Actually Works
Griffin AI moves beyond scan-and-alert to autonomously generate, test, and propose vulnerability fixes. How Safeguard's remediation engine reduces mean time to fix without introducing new risk.
Anthropic's Mythos Vulnerability Scanner: An Honest Assessment of Strengths, Weaknesses, and Reasons to Be Cautious
Anthropic's Mythos model is generating buzz for AI-powered vulnerability detection. We break down what it does well, where it struggles, and why security teams should approach the results with healthy skepticism.
AI Deepfake Phishing Campaigns in 2025: When Seeing and Hearing Isn't Believing
AI-generated voice and video deepfakes powered a new wave of phishing campaigns in early 2025. The technology is cheap, the results are convincing, and defenses are lagging.
Griffin AI: Your Autonomous Supply Chain Security Analyst
Griffin is Safeguard's AI assistant that answers natural-language questions about your software supply chain, correlates threats in real time, and recommends actions.
AI Model Poisoning: Detection Techniques for the Software Supply Chain
Poisoned AI models are a supply chain threat that traditional security tools can't detect. Here are the emerging techniques for identifying compromised models.
AI Models in Your Supply Chain: The Security Risks Nobody Talks About
AI/ML models are the new open source libraries. Here's why your supply chain security strategy needs to account for model provenance, poisoning, and compliance.
SBOMs for AI/ML Models: Why Machine Learning Needs a Bill of Materials
As AI models become critical infrastructure, the need for transparency about their components, training data, and dependencies grows urgent. Emerging standards are beginning to address this gap.
Auditing AI-Generated Code: A Practical Security Guide
AI code generation tools are producing millions of lines of code daily. Here is a practical framework for auditing AI-generated code for security vulnerabilities and supply chain risks.
AI Code Review for Security: How Effective Is It Really?
AI-powered code review tools promise to catch vulnerabilities faster than humans. We tested the claims against reality.
Self-healing security runs on Safeguard.
Your first fix PR is minutes away.
No sales call required, even your agent can complete the purchase over MCP.