# Security for AI Security for AI is a branch of cybersecurity focused on protecting AI stacks, systems, data, and applications from threats. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Identity Security for AI DevFeed: [Identity Security for AI]() Original publisher: [Read original article]() Author: info@goteleport.com (Ben Arent) Published: 2026-07-21T00:00:00Z Content type: article Language: en Sources: [Teleport]() Topics: [Security for AI](), [Security](), [Artificial Intelligence](), [Authorization]() Tags: [agents](), [ai](), [ai-agents](), [github](), [identity](), [least-privilege](), [llms](), [permissions](), [secrets](), [security](), [security-for-ai]() ### AI overview The article examines identity-security challenges created by AI agents that can act continuously with delegated access. It connects traditional risks such as broad permissions, credential sprawl, insider threats, and long-lived secrets with emerging risks from agents, sub-agents, and LLM capabilities, and advocates delegated, ephemeral, least-privilege access. ### Source excerpt AI agents run 24/7 with the same infrastructure access as your engineers. See how Teleport secures AI with cryptographic identity, audit, and trusted runtimes. ## A Note to Our Customers and Partners DevFeed: [A Note to Our Customers and Partners]() Original publisher: [Read original article]() Author: Ken MacAskill Published: 2026-06-24T13:00:00Z Content type: opinion Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Artificial Intelligence](), [Securing AI](), [Security for AI](), [Security](), [Vulnerabilities](), [agent observability]() Tags: [ai](), [ai-agents](), [ai-security](), [anthropic](), [blog](), [cursor](), [openai](), [security](), [software](), [vulnerabilities]() ### AI overview Snyk outlines an AI-focused organizational shift, continued investment in existing products, and workforce reductions. It describes its AI Security Platform for securing code, models, and intelligent systems, including visibility for AI assets, protection for AI agents, and planned offensive security for AI-era applications. ### Source excerpt A note to our customers and partners about Snyk's AI transformation and organizational changes. ## Secure by Design: The Future of Threat Modeling for AI-Native Applications DevFeed: [Secure by Design: The Future of Threat Modeling for AI-Native Applications]() Original publisher: [Read original article]() Author: John Carione Published: 2025-11-11T05:00:00Z Content type: opinion Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Security](), [Security for AI](), [Architecture & Design](), [Artificial Intelligence](), [snyk](), [Vulnerabilities](), [prompt injection]() Tags: [agentic](), [ai](), [prompt-injection](), [secure-by-design](), [security](), [security-for-ai](), [snyk]() ### AI overview This Snyk article argues that traditional, manual threat modeling cannot keep pace with AI-native applications built from large language models, autonomous agents, APIs, and changing data flows. It presents continuous, automated, AI-assisted threat modeling as a way to maintain secure-by-design systems and address risks such as prompt injection, data exfiltration, data poisoning, and agentic vulnerabilities. ### Source excerpt Explore how Snyk's Evo Threat Modeling Agent automates and contextualizes security for AI-native applications, addressing prompt injection, data exfiltration, data poisoning, and agentic vulnerabilities. ## Find, auto-fix, and prioritize intelligently, with Snyk's AI-powered code security tools DevFeed: [Find, auto-fix, and prioritize intelligently, with Snyk's AI-powered code security tools]() Original publisher: [Read original article]() Author: Liqian Lim (林利蒨) Published: 2024-10-24T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Application Security](), [snyk-code](), [Vulnerabilities](), [Security for AI](), [Large Language Model]() Tags: [ai](), [ai-coding](), [application-security](), [awareness](), [blog](), [code-security](), [llm](), [pmm](), [security](), [snyk](), [snyk-code](), [vulnerabilities]() ### AI overview The article presents Snyk Code's Snyk AgentFix, an AI-powered feature that automatically fixes code vulnerabilities. It explains how Snyk combines developer-first application security, IDE-based detection, intelligent prioritization, and automated remediation to address insecure AI-generated code at scale. ### Source excerpt Snyk Agent Fix is a powerful AI-driven tool that automatically fixes code vulnerabilities. It integrates seamlessly into developer workflows and prioritizes critical issues. By leveraging AI, Snyk Agent Fix offers fast, accurate, and safe auto-fixing, empowering teams to improve application security. ## Infosec Europe session: 4 tips for safer AI adoption DevFeed: [Infosec Europe session: 4 tips for safer AI adoption]() Original publisher: [Read original article]() Author: Gerald Crescione Published: 2024-08-01T13:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Artificial Intelligence](), [Security for AI](), [Application Security](), [Large Language Model](), [Testing](), [AI Development](), [Security]() Tags: [ai](), [ai-adoption](), [awareness](), [blog](), [customer](), [devops](), [executive](), [hallucinations](), [megawatt](), [security](), [security-for-ai](), [snyk](), [testing]() ### AI overview The article presents four takeaways for safer AI adoption, focusing on classifying AI use by business impact, prioritizing high-risk areas, using AI guardrails, testing AI-generated information and code, and involving humans in high-risk decisions. It warns that AI tools can produce insecure code suggestions, library hallucinations, and deceptive rationales. ### Source excerpt 4 takeaways about adopting AI securely from a session at Infosec Europe 2024. ## Chainguard joins Coalition for Secure AI with OpenAI, Google, Anthropic DevFeed: [Chainguard joins Coalition for Secure AI with OpenAI, Google, Anthropic]() Original publisher: [Read original article]() Published: 2024-07-18T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [ai security](), [supply-chain-security](), [Security for AI](), [Security](), [Open Source]() Tags: [ai-security](), [amazon](), [anthropic](), [chainguard](), [cisco](), [coalition-for-secure-ai](), [cohere](), [cosai](), [google](), [ibm](), [intel](), [microsoft](), [nvidia](), [oasis-open](), [openai](), [provenance](), [secure-by-design](), [software-supply-chain-security](), [standards](), [wiz]() ### AI overview Chainguard joins the Coalition for Secure AI (CoSAI) as a founding member alongside major technology companies. The coalition aims to develop open-source methodologies, standardized frameworks, and practical tools for Secure-by-Design AI systems, with initial workstreams covering AI software supply-chain security, cybersecurity integration, and AI security governance. ### Source excerpt Chainguard joins the Coalition for Secure AI with OpenAI, Google, and Anthropic, enhancing AI security. Discover our commitment to safeguarding AI technologies.