# Securing AI Published articles for Securing AI. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## CrowdStrike SafeMind Uses Adversarial Co-Evolution to Improve AI-Powered Cybersecurity DevFeed: [CrowdStrike SafeMind Uses Adversarial Co-Evolution to Improve AI-Powered Cybersecurity]() Original publisher: [Read original article]() Author: Ioana Croitoru - Sean Pagano - Keegan Hines - Alexander Nazarian - Chase Midler Published: 2026-09-18T01:40:54.157408Z Content type: article Language: en Sources: [Blog]() Topics: [Security](), [Artificial Intelligence](), [Machine Learning, Security Attacks](), [Architecture & Design]() Tags: [agent](), [ai](), [architecture](), [cyber](), [scale](), [securing-ai](), [security]() ### AI overview CrowdStrike describes SafeMind, a closed-loop cybersecurity system in which offensive and defensive AI agents continuously test and improve one another. The system is designed to generate attacks, strengthen defenses, and automate detection creation at scale. ### Source excerpt SafeMind is a closed-loop system where offense and defense continuously sharpen each other, resulting in a defense that's been forged against the best possible attacks. Learn more! ## Agents of Chaos: A New $100K Agentic Security Challenge DevFeed: [Agents of Chaos: A New $100K Agentic Security Challenge]() Original publisher: [Read original article]() Author: Vanessa Villa - John Gamble Published: 2026-09-12T11:17:51.295154Z Content type: article Language: en Sources: [Blog]() Topics: [Security](), [prompt injection](), [AI Agent]() Tags: [agentic](), [agentic-security](), [ai](), [ai-agent](), [ai-agents](), [attacks](), [competition](), [prompt-injection](), [securing-ai](), [security](), [techniques]() ### AI overview CrowdStrike is launching Agents of Chaos, an online game and AI red-teaming competition with a $100,000 prize pool. Players interact with real AI agents in an adversarial world, attempting to manipulate them and exploit gaps between their intended behavior and their actual behavior across three increasingly sophisticated acts. ### Source excerpt Agents of Chaos, CrowdStrike's new AI red teaming competition, tests players' defensive skills against adversarial AI techniques. ## Benchmaxxing: When the Benchmark Becomes the Target DevFeed: [Benchmaxxing: When the Benchmark Becomes the Target]() Original publisher: [Read original article]() Author: Nathan Danneman Published: 2026-09-12T11:17:51.295154Z Content type: article Language: en Sources: [Blog]() Topics: [Benchmark](), [Artificial Intelligence](), [Cybersecurity](), [Ground truth / benchmark quality](), [Detection engineering]() Tags: [ai](), [ai-and-cybersecurity](), [benchmark](), [benchmarking](), [benchmarks](), [blog](), [cybersecurity](), [leaderboards](), [securing-ai](), [security](), [validation]() ### AI overview The article explains how public AI and cybersecurity benchmarks can become targets for optimization, a practice it calls "benchmaxxing." It argues that gaming, ceiling effects, data leakage, binary scoring, omitted costs, and aggregate scores can make benchmark results poor proxies for real-world defensive capability. The article proposes task-coupled internal benchmarks intended to evaluate end-to-end cyber agents and support rigorous science rather than visibility-driven score optimization. ### Source excerpt The more attention a benchmark receives, the stronger the incentive to optimize for it. In AI and cybersecurity, this can have significant consequences. ## CrowdStrike Falcon Guardian Defines the Next Generation of AI Security DevFeed: [CrowdStrike Falcon Guardian Defines the Next Generation of AI Security]() Original publisher: [Read original article]() Author: Michael Devins Published: 2026-09-12T11:17:51.295154Z Content type: release Language: en Sources: [Blog]() Topics: [AI Bots]() Tags: [agentic](), [agents](), [ai](), [ai-agent](), [ai-agents](), [ai-gateway](), [ai-security](), [architecture](), [autonomous](), [platform](), [securing-ai](), [security](), [telemetry](), [threat-detection]() ### AI overview CrowdStrike announces Falcon Guardian, an AI detection and response solution for discovering, monitoring, investigating, and securing AI agents at runtime. It adds an AI gateway and connects agent activity with endpoint telemetry to support threat response. ### Source excerpt A new flagship AI detection and response solution delivers runtime protection for AI agents, introduces a new AI gateway, and extends expert-led defense. ## Introducing the CyberAgents Exchange AI Inspector: Rigorous review for community-built AI DevFeed: [Introducing the CyberAgents Exchange AI Inspector: Rigorous review for community-built AI]() Original publisher: [Read original article]() Author: Mark Beblow Published: 2026-09-09T13:00:00Z Content type: article Language: en Sources: [Tenable Blog]() Topics: [Securing AI](), [Cybersecurity](), [Large Language Model](), [open-source-security](), [Model Context Protocol (MCP)]() Tags: [agentic-ai](), [cybersecurity](), [mcp](), [open-source](), [openai](), [review](), [securing-ai]() ### AI overview Tenable introduces the CyberAgents Exchange AI Inspector, a security-review process for submissions to its registry of AI agents, skills, MCP servers, and multi-agent playbooks. It combines GPT Cyber models, Tenable security expertise, and human oversight to apply deeper review to higher-risk submissions. ### Source excerpt Open-source registries for AI agents are only effective when they include a rigorous, transparent security review process for community submissions. That's why for its new CyberAgents Exchange registry, Tenable paired its exposure management expertise with OpenAI GPT Cyber models to create the CyberAgents Exchange AI Inspector. Key takeaways The Exchange Inspector combines Tenable's exposure detection with OpenAI's GPT Cyber models and with human oversight to rigorously vet submissions made to the CyberAgents Exchange. Securing AI agents requires analyzing a broad attack surface that includes LLM instructions, tool-chaining permissions, and prompt injection risks, going far beyond traditional software security. The CyberAgents Exchange inspection process dynamically matches the appropriate AI model tier to each submission's risk level, ensuring comprehensive vetting without excessive computational overhead. Recently at OpenAI's "Intelligence at Work: Cyber Summit," Tenable and OpenAI announced a groundbreaking review process to vet the security of open-source AI agents, skills, MCP servers, and multi-agent playbooks, building on our June partnership. The new CyberAgents Exchange AI Inspector, which is built into our CyberAgents Exchange registry, will help security teams adopt agentic AI quickly and confidently. Powered by Tenable, the CyberAgents Exchange is a purpose-built, cybersecurity-native registry for AI agents, skills, MCP servers, and multi-agent playbooks. Launched in August as an open source and vendor-agnostic registry, the CyberAgents Exchange has already grown to host more than 100 AI listings, including a wave of contributions created at Tenable's SWARM build event at Black Hat USA. From the CyberAgents Exchange's inception, we understood the importance of a rigorous, comprehensive review process for agents submitted by contributors. Every submission to the CyberAgents Exchange gets a baseline review prior to being listed. Now, we are further strengt ## Open Models and Open Weights Are Foundational to Secure AI DevFeed: [Open Models and Open Weights Are Foundational to Secure AI]() Original publisher: [Read original article]() Author: andrewb@proximabiz.com (The Linux Foundation) Published: 2026-07-27T13:24:44Z Content type: opinion Language: en Sources: [Linux Foundation - Blog]() Topics: [Artificial Intelligence](), [Open Source](), [Securing AI](), [AI research agents]() Tags: [agent](), [ai](), [ai-ml](), [cisco](), [dell](), [ibm](), [meta](), [microsoft](), [nvidia](), [open-source](), [securing-ai]() ### AI overview The Linux Foundation describes its participation in the Open Secure AI Alliance with NVIDIA and other members. The alliance promotes open tools for testing, tracing, auditing, and governing AI systems, and argues that open models and open weights can support safer, more transparent, and broadly accessible AI. ### Source excerpt The Linux Foundation celebrates collaborative efforts to build and enhance the open tools and techniques that keep AI systems safe and secure. ## Announcing Agentic Development Security (ADS) DevFeed: [Announcing Agentic Development Security (ADS)]() Original publisher: [Read original article]() Author: Daniel Berman Published: 2026-06-23T04:00:00Z Content type: release Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Securing AI](), [Application Security](), [AI Agent](), [AI Development](), [Model Context Protocol (MCP)](), [MCP Server](), [ai-coding]() Tags: [agentic](), [ai](), [ai-agent](), [ai-coding](), [application-security](), [awareness](), [blog](), [developer](), [devops](), [enablement](), [executive](), [interest](), [mcp](), [mcp-server](), [securing-ai](), [security](), [snyk-platform](), [software-development](), [supply-chain-security](), [tech]() ### AI overview Snyk announces Agentic Development Security (ADS), an Evo solution for securing AI-driven software development. It embeds visibility, governance, and control into workflows where AI agents use tools, execute actions across systems, and generate production-ready code. ### Source excerpt Announcing Snyk Agentic Development Security, a new Evo solution that helps organizations securely adopt AI-driven development with visibility, governance, and control. ## Securing AI agents and tool calls DevFeed: [Securing AI agents and tool calls]() Original publisher: [Read original article]() Author: Alexander Nohe Published: 2025-12-02T19:00:00Z Content type: tutorial Language: en Sources: [Firebase Blog]() Topics: [Securing AI](), [prompt injection](), [AI Agent](), [Loop Engineering](), [App]() Tags: [agentic](), [ai](), [ai-agent](), [app-check](), [authentication](), [firebase](), [genkit](), [go](), [least-privilege](), [prompt](), [prompt-injection](), [securing-ai]() ### AI overview This article explains how prompt injection can manipulate AI agent tool calls to access unauthorized user data. It recommends using application context and least-privilege access when designing tool definitions. ### Source excerpt Beyond authentication: Learn how to secure your AI agent's tool calls from prompt injection by using application context and the principle of least privilege. ## What an 'Aha' Moment with an Org Admin Token Taught One DevSecCon Speaker About AI Security DevFeed: [What an 'Aha' Moment with an Org Admin Token Taught One DevSecCon Speaker About AI Security]() Original publisher: [Read original article]() Author: Alysa Turner Published: 2025-09-04T04:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [AI Chat](), [AI Bots]() Tags: [agentic-ai](), [agents](), [ai](), [ai-security](), [attacks](), [blog](), [customer](), [devops](), [devsecops](), [interest](), [llms](), [mcp](), [sdlc](), [securing-ai](), [security](), [supply-chain]() ### AI overview An interview preview discusses securing AI tools in software pipelines, focusing on MCP servers and agents as a supply-chain attack surface and on approaches to mitigate their risks. ### Source excerpt Discover key insights from DevSecCon speaker Brett Smith on securing AI in your pipelines. Register for DevSecCon 2025 to enhance your AI security knowledge. ## Secure at Inception: Introducing New Tools for Securing AI-Native Development DevFeed: [Secure at Inception: Introducing New Tools for Securing AI-Native Development]() Original publisher: [Read original article]() Author: Daniel Berman; Liran Tal Published: 2025-08-04T04:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Securing AI](), [Model Context Protocol](), [Artificial Intelligence](), [Vulnerabilities](), [snyk]() Tags: [agentic-security](), [agents](), [ai](), [ai-security](), [application-security](), [awareness](), [blog](), [ci-cd](), [compliance](), [customer](), [developer](), [devrel](), [devsecops](), [mcp](), [mcp-server](), [open-source-security](), [pmm](), [securing-ai](), [security](), [security-vulnerabilities](), [snyk]() ### AI overview Snyk introduces three capabilities at Black Hat 2025 for securing AI-native development: security testing embedded in agentic workflows and tools, AI-BOM visibility and governance, and MCP-scanning capabilities. The article describes emerging risks including prompt injection, model poisoning, and MCP rug pulls. ### Source excerpt Snyk unveils innovations at Black Hat to secure AI development. Features include MCP Server for agentic workflows, AI-BOM for visibility, and Toxic Flow Analysis for novel AI threats. ## Securing GenAI Development with Snyk DevFeed: [Securing GenAI Development with Snyk]() Original publisher: [Read original article]() Author: Liqian Lim (林利蒨) Published: 2025-01-09T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [genai](), [Application Security](), [ai-coding](), [Vulnerabilities](), [Security](), [ChatGPT](), [Cloudflare]() Tags: [ai](), [ai-coding](), [ai-tools](), [awareness](), [blog](), [chatgpt](), [cloudflare](), [coding](), [cves](), [developer](), [developers](), [development](), [genai](), [megawatt](), [securing-ai](), [security](), [security-solutions](), [snyk](), [solutions](), [speed](), [vulnerabilities](), [workflows]() ### AI overview This article explains how AI-generated code and AI coding assistants are changing developer workflows while creating security risks for AppSec teams. It describes the prevalence of tools such as ChatGPT and Copilot, the vulnerabilities that can appear in generated code, and the need for guardrails and security solutions such as Snyk. ### Source excerpt AI-generated code is impacting how AppSec teams work. Learn more about the risks of AI-generated code and how Snyk can help secure your codebase.