InfoQ Homepage AI Security Content on InfoQ
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Chainguard Launches Secure Workspaces and Checks for AI Coding Agents
Software supply chain security company Chainguard has announced two beta products for running and testing code written by developers and AI agents. Chainguard Workspaces provides remote development environments based on hardened microVMs, while Chainguard Checks moves continuous integration into the development loop. The company announced both products at its Assemble London event.
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Meta Extends Confidential Computing to AI Glasses with Private Processing
Meta has extended Private Processing to AI glasses, using confidential VMs, trusted execution environments, remote attestation, anonymous credentials, OHTTP routing, and TEE-based storage to process AI workloads and persistent user context in the cloud.
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Cloudflare Uses an AI Harness to Probe and Harden its WAF
Cloudflare placed frontier AI models inside a controlled testing harness to probe its Web Application Firewall (WAF), using blocked attacks as starting points for models to generate and refine new variations.
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New Archestra's OpenAPPA Saturates Two Major Security Benchmarks with a 0% Attack Success Rate
Archestra released OpenAPPA, an open-source security engine designed to stop data exfiltration caused by prompt injection or model hallucination. The team reports zero successful attacks when running security benchmarks Bench-Corp (20 multi-step enterprise workflows) and AgentThreatBench, versus 10% for Claude Code’s auto mode and 31% for Microsoft FIDES.
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AI Agents Are Disrupting Open Source Security Disclosure
A recent article by Anil Madhavapeddy argues that AI agents can turn publicly available clues about software vulnerabilities into working exploits, reducing the effectiveness of traditional disclosure embargoes in open source projects. The author highlights the need for faster patching and release processes as the time between vulnerability disclosure and exploitation shrinks.
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Docker Cloud Sandboxes Provide a Consistent Sandbox Abstraction across Laptop and Cloud
Docker Cloud Sandboxes provide secure, hosted execution environments for running AI coding agents on Docker-managed infrastructure. Built on hardware-enforced microVM isolation, the platform provides a consistent execution environment and unified CLI workflows for seamlessly moving workloads from local machines to the cloud.
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Un-Mused: How a Single Debug Setting Bypassed macOS Security in Meta’s AI Client
Security researcher Patrick Wardle revealed an unpatched zero-day vulnerability in Meta's Muse desktop client for macOS. This flaw lets unprivileged software manipulate the assistant's extensive permissions, compromising input confidentiality and account security. Despite a hotfix from Meta, the vulnerability raises significant concerns about platform trust and security boundaries.
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Repeated VM Escapes By GPT-5.6-Cyber Based Agents Prove VMs and OS' Require Better Maintenance
Traditional virtual machines are inadequate for isolating cyber-capable autonomous agents. Tests using GPT-5.6-Cyber indicated multiple escape attempts due to kernel flaws. While Firecracker provided some containment, vulnerabilities remained. The study underscores the need for minimal attack surface virtualisation technologies and rapid, proactive patching strategies to safeguard host systems.
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GitLab Warns That AI Agent Sandboxes Are Only as Secure as Their Network Access
GitLab warns that isolating an AI coding agent in a sandbox does not necessarily make the agent safe. In a new security analysis, the company describes an internal evaluation in which an AI agent escaped its sandbox by exploiting a vulnerable package proxy that had been explicitly placed on the sandbox's allowlist.
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How Figma Uses AI Agents for Security
The engineering team at software company Figma recently documented how they built AI agents to help their security team investigate alerts, search past incidents, check company systems, and even prepare code fixes. The agents learn from previous investigations, reducing repetitive work and helping engineers resolve complex alerts about 70% faster.
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Beyond Zero: Google Publishes Successor to BeyondCorp
In a recent research paper, Google introduced Beyond Zero, a “security model for the AI era” that extends Zero Trust to autonomous AI agents. The new approach moves access decisions from the application level to individual resources and actions, combining static authorization controls with dynamic AI-driven decisions to enable machine-speed enforcement for humans and agents.
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DoorDash’s Flux Runs 130,000 Engineering Tasks through Cloud-Based Agents
DoorDash has moved engineering agent workloads from developer laptops to its Flux cloud platform. The platform automated 130,000 engineering tasks in one month and supports more than 25,000 automated code reviews weekly. Flux uses isolated Firecracker microVMs, an MCP gateway, reusable playbooks, and multiple invocation surfaces to run agent workflows with scoped access and centralized auditing.
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Microsoft Moves AI Governance from Policy to Runtime Enforcement
Microsoft has outlined an AI governance architecture spanning nine governance domains and four functions: policy, control, visibility, and proof. The approach connects policies with runtime enforcement, continuous evaluation, observability, identity, security, and audit evidence to help organizations verify governance requirements as AI applications and agents operate in production.
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Cloudflare OS: Cloudflare's Open-Source Corporate AI Platform Built on a Capability-Based Model
Cloudflare recently open-sourced Cloudflare OS. It allows enterprise teams to output work artifacts grounded in enterprise knowledge, know-how, and provisioned connectors, automate repetitive workflows with optimized token cost (with AI assistance only where needed), and build personal, shareable, customizable work software that caters to specific, complex use cases within a secure sandboxed model
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InfoQ Opens Enrollment for New AI-Assisted Engineering Online Certification Program
InfoQ has opened enrollment for the InfoQ Certified AI-Assisted Engineering Program, a five-week online certification program for senior engineers and architects who already run a coding agent against production code daily, where the open questions have moved past prompting into what the agent is allowed to touch and what catches its mistakes before a human does.