ai-security
Safeguard articles tagged "ai-security" — guides, analysis, and best practices for software supply chain and application security.
593 articles
Why Traditional SAST Tools Struggle to Analyze Agentic Co...
Agentic codebases build call graphs at runtime, defeating static analysis. Here's why SAST tools miss prompt injection and tool-schema risks—and how Safeguard closes the gap.
Why Every AppSec Vendor Suddenly Has an 'AI Trust' Product
AppSec vendors are rebranding as "AI Trust" platforms. We look at the standards, M&A, and real incidents driving the shift — and why it's a supply chain problem at its core.
AI Code Detector: How It Works and Where It Fails
An AI code detector estimates whether source code was machine-generated. Here is how these tools work, why they misfire, and where security teams should and should not rely on them.
Hacking AI: How Attackers Target Machine Learning Systems
Hacking AI is not science fiction; it is a growing set of concrete techniques that exploit how models learn, process input, and produce output. Here is how to think about defending against them.
What OpenAI and Anthropic Ecosystem Partnerships Signal A...
OpenAI and Anthropic's expanding ecosystem deals are an AI model vendor security partnership signal AppSec teams can no longer afford to ignore.
The Rise of 'Security for AI' as a Distinct Product Category
Security for AI has become its own product category—backed by NIST, OWASP, and MITRE frameworks and real M&A. Here's why it's really a supply chain problem.
Claude, GPT, and Coding Harness Security: Comparing Model...
Claude and GPT both write vulnerable code by default in coding harnesses. Comparing model behavior, then Safeguard's approach versus Endor Labs' reachability-first SCA.
AI-Based Cybersecurity Tools: What to Look For
AI based cybersecurity tools range from genuinely useful triage assistants to thin wrappers around a generic model, and the difference is usually visible in how the tool handles context, not in its marketing.
MCP Architecture Explained: A Security Guide
The Model Context Protocol connects AI models to tools and data through a client-server design. Understanding that architecture is the first step to securing it.
Define Agentic: What 'Agentic' Really Means for Security
To define agentic: it describes AI systems that plan and take actions toward a goal with limited human oversight. Here is what that autonomy means for security teams.
AI Security Apps: What They Do and How to Evaluate Them
An AI security app uses machine learning to detect, prioritize, or remediate security issues. Here is what the category actually delivers and how to judge one.
How to Choose an AI Cybersecurity Company in 2026
An AI cybersecurity company uses machine learning to detect, prioritize, and remediate threats faster than rules alone. Here is how to evaluate one honestly.
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