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.
MCP-led agent workflows hand real tools to a language model. That power is also the attack surface. Here is how tool poisoning works and how to defend against it.
Every secret that touches an agent's context window is a secret the agent can leak. Just-in-time credential brokers, scoped-token issuance, and redaction layers keep the surface small without breaking the agent's ability to do real work.
A practical look at supply chain threat detection: the signals that reveal a compromised dependency, build system, or update channel, and how to catch them early.
A grounded look at what platforms are using cybersecurity AI today — across SOC tooling, code scanning, and supply-chain security — and how to tell real capability from marketing.
Claude Code skills package instructions and scripts an AI agent runs on your behalf. That power is also the risk. Here is how to vet and sandbox them.
A software supply chain security solution secures every component that flows into your builds, from open-source dependencies to CI pipelines and artifacts. Here is what one should actually do.
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.
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.
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.
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