ai-security
Safeguard articles tagged "ai-security" — guides, analysis, and best practices for software supply chain and application security.
593 articles
AI for Cyber Security: What Works and What Is Hype
AI for cyber security is real where it triages signal at machine scale, and overstated where vendors promise autonomous defense. Here is how to tell the two apart.
Pattern Scanners Can't Find Zero-Days. This Can.
Signature-based scanners only know what other people have already named. Here is the architectural reason they cannot find zero-days, and what actually does.
AI Agent Supply Chain Attacks: 2026 Trend Watch
AI agents pull tools, models, and data from a sprawling chain of upstream providers. In 2026 attackers learned to poison that chain — and the fallout is shaping how enterprises buy and operate agentic systems.
Model Context Protocol Permissions Model Explained
MCP's permissions model is subtle. Here is a careful walkthrough of how tool scoping, sampling, and resource access actually work in production.
Securing MCP Servers Without Killing Developer Velocity
MCP servers are spreading inside engineering orgs faster than security teams can review them. Here is how to govern them without slowing teams down.
Why LLMs Are Structurally Insecure (and What That Means for Your Pipeline)
Language models are not insecure because of a bug you can patch. They are insecure by construction — non-deterministic, context-poisonable, and unreproducible. Here is how to reason about them without pretending otherwise.
MCP Server Authentication and Authorization: Securing the AI Tool Layer
The Model Context Protocol enables AI agents to interact with external tools and data sources. Securing MCP servers requires authentication, authorization, and input validation patterns specific to the AI agent context.
Auto-PR Remediation Without Broken Builds
Automated fix pull requests sound great until half of them fail CI. Here is how to ship auto-PR remediation that keeps the green build, every time.
DSPM for AI: navigating data and AI compliance regulations
DSPM for AI closes the gap traditional tools miss: tracking sensitive data through embeddings, fine-tuning, and vector stores to meet EU AI Act and Colorado AI Act requirements.
Pervasive AI Security: Protecting AI That Is Everywhere in Your Stack
Pervasive AI means models embedded in nearly every application and workflow. That ubiquity creates a security surface most programs have not mapped. Here is how to think about it.
API Surface Reviewed: Griffin AI vs Mythos
Most platform comparisons stop at features. The API surface is where automation and integration actually happen — and where vendors quietly diverge.
Why LLM-Based Vulnerability Scanning Needs More Than a Single Model
Large language models are being used to find vulnerabilities in open-source code. But a single model, no matter how capable, isn't enough. Here's why multi-agent orchestration, structured CWE analysis, and deep context matter more than model size.
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