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AIR raises $50M to help companies vet the skills and add-ons AI agents use
AI security startup AIR exits stealth with $50M across two seed rounds to continuously vet skills, plugins, and MCP servers used by enterprise AI agents.
AIR, founded by Unit 8200 veterans Yair Saban and Niv Hoffman, raised $10 million led by Sequoia and $40 million led by Greenoaks to secure the emerging AI agent software supply chain. Its platform discovers agents in enterprise environments, intercepts their actions, and continuously vets skills, add-ons, and MCP servers against a maintained whitelist, filtering out about 27% of found add-ons. The company claims over 20 customers, roughly a quarter large enterprises, with strong demand in financial services and pharma, and competes with Noma Security, Zenity, Astrix Security, and Operant AI.
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Securing Claude Code: The New Compliance API, Local Visibility, and Identity Governance
Anthropic's new Compliance API endpoints expose Claude Code local session transcripts, highlighting governance gaps for endpoint AI agents.
Anthropic added local session transcript endpoints to its Compliance API on August 11, 2026, giving security teams visibility into prompts, bash commands, file operations, and MCP commands run by Claude Code harnesses on endpoints. The article argues local harnesses break the classic shared-responsibility model, citing Token Security data that 68.6% of discovered AI agents run on endpoints, and a Cloud Security Alliance survey of 418 IT and security professionals in which 82% found an unknown agent within the past year. It outlines three governance layers: Anthropic managed settings as a policy baseline, the Compliance API for cloud-visible transcripts, and endpoint telemetry to connect agent activity to identity, credentials, and permissions.
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10 most critical LLM vulnerabilities
OWASP updated its Top 10 LLM application vulnerabilities, ranking prompt injection first and elevating excessive agency to third amid agentic adoption.
OWASP refreshed its Top 10 list of critical vulnerabilities in LLM applications, for the first time incorporating real-world incident data alongside expert voting. Prompt injection and sensitive information disclosure remain first and second, while excessive agency jumped from sixth to third as agentic systems that call APIs and execute code proliferate. Unbounded consumption of AI resources rose in prominence, while improper output handling dropped to the bottom as output sanitization becomes widespread. The list includes remediation guidance such as strict output schemas, human-in-the-loop approvals, and least-privilege credentials held in application code.
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HOL Guard: Open-source antivirus for AI agents
HOL Guard is an open-source local guardrail that pauses AI coding agents before risky actions like secret access and prompt injection.
HOL Guard sits between AI coding agents (Claude Code, Cursor, Codex, Gemini CLI and others) and the host machine, intercepting risky commands before execution with checks taking under 50 milliseconds and running fully offline. It offers four sensitivity modes — Gentle, Balanced (default), Strict, and Paranoid — and parses command structure, environment, sensitive-path access and network destinations to decide when to interrupt. The core runtime is free and open source on GitHub, with 552,000 downloads reported; the vendor says it has no telemetry on adoption because collection is off by default.
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How to Secure Enterprise AI: From Adoption to Incident Readiness
Sygnia-backed guidance urges a lifecycle approach to enterprise AI security, citing survey data that AI adoption is outpacing governance and incident readiness.
The Hacker News published Sygnia-sponsored guidance on securing enterprise AI across its lifecycle, from use-case definition and vendor selection to deployment and incident readiness. It cites Sygnia's 2026 CISO survey of 600 senior leaders: 63% expect AI fully embedded by 2027, 73% say their organization would not be fully ready for a significant cyberattack, and 67% of executives believe unapproved AI tools already caused a breach. The piece highlights shadow AI, ad hoc integrations, and over-permissioned AI agents as key attack surface risks, noting only 38% of organizations report a comprehensive AI policy.
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Introducing the Agents API
OpenAI launched the Agents API in public beta, exposing the Codex agent harness, managed sandboxes, and multi-agent orchestration to developers.
OpenAI introduced the Agents API in public beta, giving developers the same agent harness and infrastructure that powers Codex through a single API call specifying task, model, tools, and environment. It supports OpenAI-managed sandboxes, customer infrastructure, or partner environments from providers including Cloudflare, Modal, E2B, Vercel, Oracle, DigitalOcean, Blaxel, Daytona and Runloop. Features include automatic context compaction for long sessions, tool search and programmatic tool calling to reduce token usage, and multi-agent support for parallel subagents. The harness is open-source Codex code; there are no extra API fees during beta, with developers paying only for tokens and tools used.
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⚡ Weekly Recap: Telecom Sleeper Cells, LLM Jailbreaks, Apple Forces U.K. Age Checks and More
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