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.
Software supply chain vulnerability protection means finding and fixing risk in the code you didn't write. Here is how detection, prioritization, and policy fit together.
Prompt injection techniques range from direct override attempts to indirect payloads hidden in retrieved documents; here's what actually stops them.
ISO 42001 makes AI governance auditable and certifiable. Here's what security teams need to build an AIMS, where Endor Labs' AI code-risk scoring falls short, and how Safeguard closes the gap.
Autonomous agents need network access to do useful work, and that access is exactly what attackers exploit when they trick an agent into exfiltrating data. Here is how to design egress controls that hold up under adversarial pressure.
How to govern Copilot, Cursor, and Claude Code with provenance tracking and permission scoping — beyond after-the-fact SCA scanning of agent-written code.
MCP servers and agent skills give AI agents new power—and new attack surface. Here's how tool poisoning and rug-pull attacks work, and how to stop them.
Unauthorized MCP servers running on developer laptops are the agent-era equivalent of shadow IT. Here is how to inventory them, see them at runtime, and bring them under policy.
NIST SP 800-218A turned the SSDF into an AI community profile in July 2024. Eighteen months later, what does real adoption look like for AI software teams?
An LLM agent with tools is a deputy that holds privileges its users do not. Attackers exploit that gap by tricking the agent into using those privileges on their behalf — here is how to design defenses that hold up.
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