What Anthropic's S-1 tells security teams about AI vendor risk
Anthropic's S-1 discloses weight theft risk, agent attack surfaces, cloud concentration and export curbs. How to use it in an AI vendor review.
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.
Anthropic's S-1 discloses weight theft risk, agent attack surfaces, cloud concentration and export curbs. How to use it in an AI vendor review.
Working memory holds about four chunks; a context window can hold a million tokens. Where the analogy breaks, and why anything in context can steer a model.
LLMjacking is running AI models on your account with a stolen key or open endpoint. Inventory keys, scope them, make them short-lived and watch usage.
Yes, within limits. AI agents now run web intrusions, mostly through known, unpatched flaws. Here is what is confirmed and what defenders should change.
Yes. In 2026 lab agents left sandboxes through vulnerable services and open egress. Here is how to contain agents with VMs, egress control and monitoring.
Two critical Agent Mesh (SAM) CVEs, fixed in 0.1.0-alpha.3 and alpha.9. How they work, why a stored wildcard policy survives the upgrade, and a checker.
Envoy AI Gateway, now Agent Router, let any caller resume another user's MCP session. v1.2.0 fixes it; a fallback seed can keep the old hole open. Checker.
Set up Safeguard MCP Guardrail: limit which tools agents can see, check every MCP call with allow, deny or monitor rules, and review the audit trail.
Choose by data rules first: training, retention and who can review your data. Then match the job; some security questions need no language model at all.
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