Guardrails for AI agents and releases, build yourself or buy?
Guardrails block unsafe agent actions and risky releases. See what a team can build with policy code and proxies, and where buying saves time and risk.
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.
Guardrails block unsafe agent actions and risky releases. See what a team can build with policy code and proxies, and where buying saves time and risk.
Common year one mistakes with AI agent identity: shared tokens, borrowed human accounts, no expiry, no inventory and no review. Each with a practical fix.
A service account is a shared credential for software. An agent identity tracks one autonomous agent, its owner and its access. Here is where they overlap.
Agent identity decides which AI agent holds which access. Use these 12 questions on credentials, scope, logs and exit terms before you buy a product.
Run a two week agent identity trial by picking three real agents, issuing separate identities, and testing revocation, scope limits and audit records.
Which numbers show that identity for AI agents works, such as owner coverage and credential age, and which flatter you, like total agents or tokens issued.
Five levels of identity for AI agents, from shared API keys to short-lived, delegated, audited access. Find your level and the next step to take.
Agent identity means knowing which AI agents hold which access. Here is how to explain the risk, the cost and the ask to a CFO or board in plain terms.
Buyer criteria for AI agent identity tools: discovery of agents, scoped credentials, audit trails, approvals and integrations. A vendor neutral checklist.
Weekly insights on software supply chain security, delivered to your inbox.
Your first fix PR is minutes away.
No sales call required, even your agent can complete the purchase over MCP.