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.
Deep dives, practical guides, and incident analyses from engineers who build Safeguard. No fluff, no vendor FUD — just what you need to ship secure software.
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 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.
MCP's permissions model is subtle. Here is a careful walkthrough of how tool scoping, sampling, and resource access actually work in production.
MCP servers are spreading inside engineering orgs faster than security teams can review them. Here is how to govern them without slowing teams down.
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.
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.
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.
Copilot, Cursor, and Claude Code change what enters your codebase and how. A practitioner's map of the real supply chain risks — hallucinated packages, rules-file injection, and unreviewed transitive trust.
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.
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