ai-security
Safeguard articles tagged "ai-security" — guides, analysis, and best practices for software supply chain and application security.
585 articles
Distinguishing Model Risk from Application Risk in Agenti...
Model flaws and application flaws in AI agents cause different breaches and need different fixes. Real incidents show where each risk actually lives — and how to test for both.
How Malicious Payloads Get Smuggled Into Trusted AI Skill...
Attackers smuggle malicious payloads into trusted AI skill repositories via typosquats, staged fetches, and split-file obfuscation — here is exactly how it works.
What an AI Model Risk Registry Should Actually Track
Most AI model inventories are name-and-owner spreadsheets. Here's the provenance, licensing, CVE, and revalidation fields a real AI model risk registry needs to track.
MCP Server Permissions: A Practical Checklist for Reducin...
A practical checklist for scoping MCP server permissions, denying risky defaults, and limiting the blast radius when an AI agent's tool access is exploited.
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.
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.
What Is Prompt Engineering? A Security Guide for LLM Applications
Prompt engineering is how you steer an LLM, and it is also where a lot of application security now lives. Here is how to write prompts that resist injection and leakage.
Artificial Intelligence Security Tools: What They Do and How to Choose
Artificial intelligence security tools now sit in two camps: tools that use AI to defend software, and tools that defend the AI itself. Knowing which one you need shapes the whole buying decision.
OWASP LLM Top 10 2025: System Prompt Leakage and Vector Weaknesses
The OWASP Top 10 for LLM Applications 2025 added System Prompt Leakage and Vector/Embedding Weaknesses, and elevated Sensitive Information Disclosure to #2. Here is the defender view.
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.
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.