# pmm Published articles for pmm. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## When a vendor's breach becomes yours: lessons from the Klue incident DevFeed: [When a vendor's breach becomes yours: lessons from the Klue incident]() Original publisher: [Read original article]() Author: Anthony Larkin Published: 2026-06-23T03:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [incident](), [Software as a service](), [Security](), [OAuth](), [data](), [Back end]() Tags: [backend](), [blog](), [breach](), [crm](), [customer](), [data](), [executive](), [incident](), [oauth](), [pmm](), [saas](), [salesforce](), [secrets](), [security](), [supply-chain-security](), [tech](), [tokens](), [vulnerability-insights]() ### AI overview The article examines how a forgotten Klue credential enabled attackers to compromise the vendor's backend, harvest OAuth tokens, access connected customer Salesforce environments, and exfiltrate CRM data. It presents the incident as an example of how a SaaS breach can cascade across downstream customers. ### Source excerpt A forgotten credential at vendor Klue let attackers reach customers' Salesforce data. How modern SaaS breaches cascade, and the keys you should audit. ## You Patched LiteLLM, But Do You Know Your AI Blast Radius? DevFeed: [You Patched LiteLLM, But Do You Know Your AI Blast Radius?]() Original publisher: [Read original article]() Author: Rudy Lai Published: 2026-04-02T04:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Artificial Intelligence](), [Large Language Model](), [Security](), [Malware](), [Open Source](), [incident](), [data](), [App](), [Code]() Tags: [agent](), [ai](), [apis](), [application-security](), [applications](), [awareness](), [blog](), [code](), [code-security](), [data](), [incident](), [interest](), [llm](), [malware](), [open-source](), [open-source-security](), [pmm](), [security](), [supply-chain-security](), [tools](), [vulnerability-insights](), [workflows]() ### AI overview LiteLLM, an open-source gateway routing requests to more than 100 LLM providers, was compromised with credential-stealing malware. The incident exposed how connected models, APIs, tools, agent workflows, and sensitive data can expand an AI system's blast radius. ### Source excerpt The LiteLLM compromise showed AI risk extends beyond dependencies. Use Evo AI-SPM to map your full AI blast radius, securing connected models, tools, and agent workflows.1 ## Building AI Security with Our Customers: 5 Lessons from Evo's Design Partner Program DevFeed: [Building AI Security with Our Customers: 5 Lessons from Evo's Design Partner Program]() Original publisher: [Read original article]() Author: Rudy Lai Published: 2026-04-01T04:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Artificial Intelligence](), [Securing AI](), [Generative AI](), [shadow AI](), [ai security](), [Security](), [Automation]() Tags: [agentic](), [agents](), [ai](), [ai-adoption](), [ai-security](), [application-security](), [aspm](), [automation](), [awareness](), [blog](), [ci-cd](), [compliance](), [customer](), [customer-featured](), [developer](), [devops](), [executive](), [finserv](), [generative](), [generative-ai](), [interest](), [pmm](), [policy](), [retail](), [scale](), [security](), [shadow-ai](), [snyk-apprisk](), [snyk-platform](), [tech]() ### AI overview Snyk shares five lessons from its Evo design partner program for securing generative AI. The article emphasizes discovering AI sprawl and shadow AI, understanding custom AI deployments, replacing static spreadsheets, enforcing governance policies, and using actionable risk intelligence to move AI from chaos to controlled production. ### Source excerpt Learn 5 key lessons from Snyk's Evo design partner program. Discover how AI discovery, risk intelligence, and policy automation help teams secure generative AI and govern AI sprawl at scale. ## From Discovery to Defense: Why AI Red Teaming Is the Next Step After AI-SPM DevFeed: [From Discovery to Defense: Why AI Red Teaming Is the Next Step After AI-SPM]() Original publisher: [Read original article]() Author: Nuno Loureiro Published: 2026-03-25T04:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Vulnerabilities]() Tags: [agentic](), [ai](), [analysis](), [attacks](), [authentication](), [awareness](), [blog](), [executive](), [interest](), [microservices](), [pmm](), [security](), [snyk-code](), [testing](), [vulnerabilities]() ### AI overview The article argues that AI red teaming should follow AI-SPM to test AI systems for prompt injection, data exposure, and behavioral vulnerabilities. It contrasts increasingly capable static code analysis with the need to test running, distributed applications where vulnerabilities can emerge across interacting components. ### Source excerpt AI red teaming is the next step after AI-SPM. Learn how Evo Agent Red Teaming simulates real attacks to uncover prompt injection, data exposure, and behavioral vulnerabilities in AI systems. ## Introducing Agent Security DevFeed: [Introducing Agent Security]() Original publisher: [Read original article]() Author: Manoj Nair Published: 2026-03-23T04:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [AI Agent](), [Securing AI](), [Artificial Intelligence](), [shadow AI](), [prompt injection](), [supply-chain-security](), [Security](), [data]() Tags: [agents](), [ai](), [ai-security](), [americas](), [application-security](), [applications](), [aspm](), [awareness](), [blog](), [ci-cd](), [code-security](), [compliance](), [developer](), [development](), [devsecops](), [executive](), [interest](), [pmm](), [production](), [prompt-injection](), [security](), [security-labs](), [shadow-ai](), [snyk-code](), [snyk-platform](), [supply-chain](), [supply-chain-security](), [tech]() ### AI overview Snyk introduces Agent Security, a unified approach to securing the AI agent lifecycle from code to runtime. The announcement presents Evo AI-SPM as a generally available foundation for inventorying, governing, and enforcing controls over AI models, agents, tools, and related risks, including shadow AI, prompt injection, data leakage, and unsafe agent actions. ### Source excerpt Introducing Agent Security, a unified approach to governing AI agents and ensuring safe behavior from code to runtime. Start with Evo AI-SPM, now generally available. ## The Next Era of AppSec: Why AI-Generated Code Needs Offensive Dynamic Testing DevFeed: [The Next Era of AppSec: Why AI-Generated Code Needs Offensive Dynamic Testing]() Original publisher: [Read original article]() Author: Nuno Loureiro Published: 2026-03-20T00:00:00Z Content type: opinion Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Application Security](), [AI-assisted coding]() Tags: [agentic](), [ai](), [analysis](), [api](), [authentication](), [awareness](), [backend](), [blog](), [code](), [executive](), [interest](), [microservices](), [pmm](), [security](), [snyk-code](), [testing]() ### AI overview The article argues that AI-driven development has outpaced security validation. It says advanced static analysis can identify potential flaws, but offensive dynamic testing is needed to determine what is exploitable in live, distributed applications. ### Source excerpt Static analysis tells you what might be vulnerable, but dynamic testing tells you what is actually exploitable. Learn why the next era of AppSec requires combining code-level context with live environment testing to secure AI-generated code. ## AI Is Building Your Attack Surface. Are You Testing It? DevFeed: [AI Is Building Your Attack Surface. Are You Testing It?]() Original publisher: [Read original article]() Author: Manoj Nair Published: 2026-03-19T00:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [code security](), [AI-assisted coding](), [Large Language Model](), [AI Bots](), [Benchmark](), [Back end](), [Code]() Tags: [agents](), [ai](), [ai-agents](), [awareness](), [benchmark](), [blog](), [code](), [code-generation](), [code-security](), [coding](), [executive](), [pmm](), [snyk-platform](), [testing]() ### AI overview AI-generated code is accelerating development while introducing serious security risks: 62% of LLM-generated backend code evaluated by BaxBench was broken or insecure, and about half of the code that worked remained exploitable. The article argues that static analysis is necessary but insufficient, and that runtime testing is needed to assess real exploitability. It also highlights AI agents as an expanding attack surface because they increasingly call privileged and undocumented APIs. ### Source excerpt Speed has outpaced validation. With 62% of LLM-generated code testing as insecure and AI agents using undocumented APIs, legacy tools fall short. Learn how Snyk's AI-powered dynamic testing secures your expanding attack surface. ## Snyk Opens San Francisco Innovation Hub DevFeed: [Snyk Opens San Francisco Innovation Hub]() Original publisher: [Read original article]() Author: Peter McKay Published: 2026-03-18T04:00:00Z Content type: news Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Responsibility & Safety]() Tags: [ai](), [ai-security](), [americas](), [awareness](), [blog](), [community](), [developer](), [developers](), [development](), [devops](), [hub](), [innovation](), [pmm](), [security](), [snyk-platform](), [snyk-team](), [tech]() ### AI overview Snyk announces a San Francisco innovation hub focused on AI security. The space will host weekly technical sessions and hackathons for Bay Area AI engineers and promotes integrating security throughout AI development. ### Source excerpt Snyk is opening a new innovation hub in downtown San Francisco, creating a strategic center of gravity for AI security. This new community space invites all Bay Area builders to join weekly hackathons and technical sessions to help shape the future of secure AI innovation. ## The 89% Problem: How LLMs Are Resurrecting the "Dormant Majority" of Open Source DevFeed: [The 89% Problem: How LLMs Are Resurrecting the "Dormant Majority" of Open Source]() Original publisher: [Read original article]() Author: Noa Yaffe-Ermoza; Liran Tal; Ezra Tanzer Published: 2026-03-04T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Large Language Model](), [ai-coding](), [supply-chain-security](), [open-source-security](), [Open Source](), [Generative AI](), [Security]() Tags: [ai](), [ai-coding](), [awareness](), [blog](), [coding](), [developer](), [devrel](), [engineering](), [generative-ai](), [interest](), [llms](), [open-source](), [open-source-security](), [pmm](), [python](), [security](), [supply-chain](), [supply-chain-security]() ### AI overview The article examines how LLM-powered coding assistants can revive abandoned and obscure open source packages by selecting them from patterns in broad training data rather than relying on popularity or maintenance signals. It argues that package health intelligence is important for identifying supply chain security risks in the open source ecosystem. ### Source excerpt AI coding assistants are resurrecting millions of abandoned open source packages. Learn how LLMs expose the "Dormant Majority" and why package health intelligence is critical for supply chain security. ## Snyk and uv, Better Together DevFeed: [Snyk and uv, Better Together]() Original publisher: [Read original article]() Author: Ryan Searle Published: 2026-02-24T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Package Management](), [Python](), [supply-chain-security](), [AI Development](), [Vulnerabilities](), [JSON](), [Maintainers](), [GitHub](), [toolchain](), [pip](), [Poetry]() Tags: [ai](), [ai-development](), [application-security](), [awareness](), [blog](), [code-security](), [developer](), [development](), [devrel](), [enablement](), [executive](), [github](), [interest](), [json](), [maintainers](), [package-management](), [pmm](), [python](), [related-content](), [sbom](), [security](), [supply-chain-security](), [toolchain](), [vulnerabilities]() ### AI overview Snyk and uv have partnered to combine uv's high-performance Python package management with supply chain security. Their collaboration adds native CycloneDX SBOM export to uv, enabling Snyk vulnerability and license-compliance testing for uv-managed projects. ### Source excerpt Snyk and uv have teamed up to provide high-performance package management with native security for Python-based AI development. Build, install, and secure your AI-native applications from inception with Snyk's native support for the uv ecosystem. ## Claude Code Security: A Welcome Evolution in the Remediation Loop DevFeed: [Claude Code Security: A Welcome Evolution in the Remediation Loop]() Original publisher: [Read original article]() Author: Manoj Nair Published: 2026-02-23T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Claude Code](), [anthropic](), [Vulnerabilities](), [AI-assisted coding](), [Application Security](), [Securing AI](), [code security](), [Large Language Model](), [Frontier AI](), [vulnerability]() Tags: [ai](), [ai-security](), [anthropic](), [application-security](), [awareness](), [blog](), [claude-code](), [code-security](), [cybersecurity](), [devops](), [devsecops](), [executive](), [frontier-ai](), [interest](), [llm](), [open-source-security](), [pmm](), [review](), [security](), [snyk-code](), [snyk-open-source](), [snyk-platform](), [tech](), [validation](), [vulnerabilities]() ### AI overview Claude Code Security is presented as a major advance in vulnerability discovery and patch drafting, but the article argues that enterprise security still requires deterministic and dynamic validation, remediation automation, and governance. It emphasizes that secure code generation remains difficult because AI-assisted development can introduce business logic, authorization, injection, and cross-file vulnerabilities. ### Source excerpt Anthropic's Claude Code Security marks a major shift in vulnerability discovery, but AI-driven development requires more than just reasoning to remain secure. Learn how Snyk's AI Security Fabric integrates with Claude to close the loop between finding vulnerabilities and fixing them at scale. ## Snyk and Cline: Securing the Future of Autonomous Coding DevFeed: [Snyk and Cline: Securing the Future of Autonomous Coding]() Original publisher: [Read original article]() Author: Carey Stanton Published: 2026-02-18T05:00:00Z Content type: news Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [agentic-coding](), [Security](), [ai-coding](), [Model Context Protocol](), [coding](), [Pull Request]() Tags: [agentic](), [agentic-coding](), [agents](), [ai](), [ai-coding](), [americas](), [application-security](), [autonomous](), [blog](), [code-security](), [coding](), [developer](), [devsecops](), [enablement](), [enterprise](), [executive](), [external](), [integration](), [interest](), [model-context-protocol](), [pmm](), [pull-request](), [reactive](), [related-content](), [review](), [scm](), [security](), [snyk-code](), [snyk-platform](), [snyk-security-intel](), [tech](), [vs-code]() ### AI overview Snyk and Cline announce a partnership to integrate enterprise security intelligence into autonomous coding workflows. Using the Model Context Protocol, Snyk Studio guides Cline's agent in real time, helping enforce security standards before generated code reaches a pull request. ### Source excerpt Snyk and Cline have partnered to integrate enterprise-grade security directly into autonomous coding loops. By bridging the trust gap, Snyk and Cline enable teams to innovate faster while maintaining rigid security and compliance standards. ## Weaving Security into the Flow: New Snyk Studio Capabilities Power the AI Security Fabric DevFeed: [Weaving Security into the Flow: New Snyk Studio Capabilities Power the AI Security Fabric]() Original publisher: [Read original article]() Author: Daniel Berman Published: 2026-02-17T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Securing AI](), [AI Development](), [Security](), [ai-coding](), [Claude Code](), [Command-line interface](), [pull-requests](), [cursor]() Tags: [ai](), [ai-development](), [ai-security](), [application-security](), [blog](), [claude-code](), [cli](), [code-security](), [cursor](), [developer](), [developer-velocity](), [devsecops](), [enablement](), [interest](), [pmm](), [pull-requests](), [scm](), [security](), [snyk-code](), [snyk-platform](), [supply-chain-security](), [vulnerability-insights](), [workflows]() ### AI overview Snyk Studio announces new capabilities for securing AI-driven development, including streamlined integrations with Gemini CLI and Claude Code, automated remediation that generates pull requests, and enterprise reporting and controls. The update embeds security into developers' existing workflows so AI-assisted code can be secured from the first prompt while supporting developer velocity and governance. ### Source excerpt Snyk Studio is redefining AI development security with new integrations for Gemini CLI and Claude Code, enabling developers to build fast without sacrificing safety. Bridge the gap between developer velocity and governance to ensure your code is secure at inception. ## The Prescriptive Path to Operationalizing AI Security DevFeed: [The Prescriptive Path to Operationalizing AI Security]() Original publisher: [Read original article]() Author: Brian Rogan Published: 2026-02-03T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Responsibility & Safety](), [AI-assisted coding]() Tags: [ai](), [ai-adoption](), [ai-coding](), [ai-security](), [automation](), [autonomous](), [awareness](), [blog](), [developer](), [devsecops](), [enablement](), [framework](), [platform](), [pmm](), [security](), [snyk-learn](), [snyk-platform]() ### AI overview This article presents the Prescriptive Path, an operating framework for applying AI-security capabilities over time. It advocates a unified platform to strengthen DevSecOps, add guardrails for AI coding assistants, and secure AI-native applications as adoption and automation grow. ### Source excerpt Learn how to move from vision to practice with the Prescriptive Path, a framework for operationalizing AI security at scale. By replacing fragmented tools with a unified platform, you can build trust and secure AI-native applications at machine speed. ## Secure by Default: Why Snyk and Augment Code are the New Standard for AI Development DevFeed: [Secure by Default: Why Snyk and Augment Code are the New Standard for AI Development]() Original publisher: [Read original article]() Author: Lindsay Kitendaugh Published: 2026-01-07T05:00:00Z Content type: release Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [AI Development](), [Security](), [supply-chain-security](), [Vulnerabilities](), [Software Engineering](), [Code]() Tags: [ai](), [ai-agents](), [ai-coding](), [ai-development](), [americas](), [awareness](), [blog](), [co-created](), [code-security](), [developer](), [devops](), [devsecops](), [engineering](), [interest](), [pmm](), [real-time](), [scale](), [security](), [snyk-code](), [snyk-security-intel](), [software-development](), [supply-chain](), [supply-chain-security](), [tech](), [vulnerabilities]() ### AI overview Snyk and Augment Code announce a partnership that embeds Snyk's security intelligence into Augment's AI-powered development workflow. The integration provides real-time code scanning, agent-led vulnerability remediation, and policy-based governance for AI-generated code. ### Source excerpt Snyk and Augment Code have partnered to deliver real-time security scanning and autonomous remediation directly within AI-powered development workflows, allowing teams to maintain peak velocity while ensuring every line of code is secure by default and compliant with organizational policies. ## The Agentic OODA Loop: How AI and Humans Learn to Defend Together DevFeed: [The Agentic OODA Loop: How AI and Humans Learn to Defend Together]() Original publisher: [Read original article]() Author: Manoj Nair Published: 2025-11-10T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Securing AI](), [ai security](), [Security](), [Artificial Intelligence]() Tags: [adaptive](), [agentic](), [agentic-security](), [agents](), [ai](), [autonomous](), [autonomous-agents](), [awareness](), [blog](), [collaboration](), [context](), [cycles](), [executive](), [false-positive](), [loops](), [model](), [pmm](), [policy](), [real-time](), [reasoning](), [security](), [systems](), [visibility]() ### AI overview This article presents the Agentic OODA Loop as a model for human and AI security engineers to defend AI-native systems. Inspired by the fighter-pilot cycle of Observe, Orient, Decide, and Act, it advocates adaptive defense that gains real-time visibility, reasons about context, automates policy enforcement and remediation with human oversight, and continuously learns from alerts, false positives, and exploit attempts. ### Source excerpt Discover how AI and human security engineers collaborate to defend against evolving threats at machine speed. Learn about the new mindset for adaptive, intelligent, and symbiotic defense in the age of Agentic AI. ## Beyond the Scan: The Future of Snyk Container DevFeed: [Beyond the Scan: The Future of Snyk Container]() Original publisher: [Read original article]() Author: Brendan Hann; Pratip Banerji Published: 2025-11-04T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [container-security](), [Vulnerabilities](), [CI/CD]() Tags: [ai](), [awareness](), [blog](), [ci-cd](), [container-security](), [developer](), [docker](), [docker-hub](), [engineering](), [monitoring](), [pmm](), [security](), [snyk-container](), [vulnerabilities]() ### AI overview Snyk outlines a developer-first vision for container security that connects the IDE, CI/CD pipeline, container registry, and production. It highlights continuous registry monitoring to identify newly disclosed vulnerabilities in previously built images. ### Source excerpt Snyk Container rethinks security, moving beyond scans to deliver a comprehensive, end-to-end solution. It connects the entire lifecycle, from IDE to production, with continuous monitoring and AI-powered remediation. ## Snyk Studio: Now for All Customers, Powering Secure AI Development at Scale DevFeed: [Snyk Studio: Now for All Customers, Powering Secure AI Development at Scale]() Original publisher: [Read original article]() Author: Daniel Berman Published: 2025-11-04T04:00:00Z Content type: news Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Artificial Intelligence](), [AI Development](), [Securing AI](), [Security](), [VS Code Extension](), [MCP Server](), [code productivity](), [FIRST]() Tags: [2025](), [ai](), [ai-coding](), [ai-development](), [ai-security](), [availability](), [awareness](), [blog](), [code](), [code-security](), [developer](), [development](), [devops](), [engineering](), [enterprise](), [extension](), [guides](), [integration](), [mcp](), [mcp-server](), [pmm](), [security](), [shift-left](), [snyk](), [speed](), [tool](), [vs-code]() ### AI overview Snyk Studio is now available to all customers as a product for securing the AI-driven development lifecycle. The announcement introduces streamlined setup through the official Snyk VS Code extension, enterprise-wide deployment, and general availability of the Snyk MCP Server integration engine. ### Source excerpt Snyk Studio now offers secure AI development at scale for all customers, with streamlined setup via VS Code extension and enterprise rollout capabilities. ## DevSecCon 2025 Recap: Securing the AI Revolution Together DevFeed: [DevSecCon 2025 Recap: Securing the AI Revolution Together]() Original publisher: [Read original article]() Author: Ben Desjardins Published: 2025-10-22T23:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Artificial Intelligence](), [DevSecOps](), [snyk](), [Application Security](), [Security](), [ide](), [Pull Request](), [snyk-code](), [Development]() Tags: [2025](), [ai](), [also](), [blog](), [developer](), [devops](), [devsecops](), [ide](), [interest](), [pmm](), [secure-software](), [security](), [snyk](), [snyk-code](), [snyk-open-source](), [snyk-platform]() ### AI overview This DevSecCon 2025 recap examines how AI is changing software development and security. It covers AI-accelerated DevSecOps, securing code from the first prompt, and managing AI-native application chaos with Evo by Snyk. The article also highlights Snyk capabilities for IDEs, pull requests, Snyk Code, and AppSec governance. ### Source excerpt AI is changing development. Our DevSecCon 2025 recap covers the 3 critical stages: AI-Accelerated DevSecOps, securing code at the first prompt, and taming AI-native app chaos with Evo by Snyk. ## Beyond the Hype: 5 Major Reasons to Attend DevSecCon 2025 DevFeed: [Beyond the Hype: 5 Major Reasons to Attend DevSecCon 2025]() Original publisher: [Read original article]() Author: Ben Desjardins Published: 2025-10-14T23:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Application Security](), [DevSecOps](), [Artificial Intelligence](), [Security](), [sdlc](), [snyk-platform]() Tags: [2025](), [ai](), [application-security](), [awareness](), [blog](), [developer](), [devops](), [devsecops](), [executive](), [pmm](), [security](), [snyk-platform]() ### AI overview This article promotes DevSecCon 2025 as a conference for development and security leaders. It focuses on managing security risks introduced by AI-generated code, improving visibility across the development lifecycle, elevating application security from reactive ticket management to strategic governance, and enabling developers with frictionless security guardrails. ### Source excerpt AI is transforming development and security. Join dev & security leaders at DevSecCon 2025 on Oct 22 to get a blueprint for secure innovation. Learn to manage AI code risks, empower developers, and elevate your AppSec strategy. ## How Snyk Learn Helps You Meet PCI DSS v4.0 Developer Training Requirements DevFeed: [How Snyk Learn Helps You Meet PCI DSS v4.0 Developer Training Requirements]() Original publisher: [Read original article]() Author: Michael Biocchi; Celia Jenkins Published: 2025-09-23T04:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [snyk-learn](), [Security](), [Vulnerabilities](), [Testing](), [Software Engineering]() Tags: [awareness](), [blog](), [compliance](), [developer](), [developers](), [pci-dss](), [pci-dss-v4-0](), [pmm](), [reviews](), [security](), [snyk-learn](), [testing](), [training](), [vulnerabilities]() ### AI overview The article explains how Snyk Learn supports PCI DSS v4.0.1 developer training requirements. It describes relevant, just-in-time security lessons linked to coding mistakes, along with training on secure coding, security testing, code reviews, and software vulnerabilities. ### Source excerpt Discover how Snyk Learn helps organizations meet PCI DSS v4.0 developer training requirements by providing relevant, just-in-time, interactive, and trackable security education for developers. ## Secure Your AI Workflows: New Governance & Visibility Features from Snyk DevFeed: [Secure Your AI Workflows: New Governance & Visibility Features from Snyk]() Original publisher: [Read original article]() Author: Kate Powers Burke; Brendan Hann Published: 2025-09-18T08:00:00Z Content type: release Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Vulnerabilities](), [Developer Tools]() Tags: [ai](), [ai-security](), [awareness](), [blog](), [cli](), [compliance](), [developer](), [devops](), [features](), [pmm](), [security](), [snyk-code](), [snyk-platform](), [vulnerabilities](), [workflows]() ### AI overview Snyk announces governance and visibility features for AppSec teams managing security risks in AI-driven development. The supplied text covers an approval workflow for ignored findings, persistence of CLI scan results, and dependency-based vulnerability grouping. ### Source excerpt Gain visibility and control over your AI-driven development. Snyk's new features help AppSec teams govern security, prioritize risks in AI-generated code, and scale your security program effectively. ## 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. ## Building AI Trust with Snyk Code and Snyk Agent Fix DevFeed: [Building AI Trust with Snyk Code and Snyk Agent Fix]() Original publisher: [Read original article]() Author: Liqian Lim (林利蒨); Brendan Hann Published: 2025-06-23T04:00:00Z Content type: news Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [snyk](), [snyk-code](), [ai security](), [Application Security](), [ai-governance](), [Securing AI](), [Pull Request](), [ide]() Tags: [ai](), [ai-coding](), [ai-governance](), [ai-security](), [application-security](), [auto-remediation](), [autonomous](), [blog](), [code-security](), [compliance](), [developer](), [devops](), [engineering](), [pmm](), [pull-requests](), [sast](), [security](), [snyk](), [snyk-code](), [snyk-platform]() ### AI overview Snyk describes its AI Security Platform, Snyk Code, and Snyk Agent Fix for governing AI-assisted development. Snyk Agent Fix autonomously generates and validates code-security fixes, offering auto-remediation in IDEs and pull requests, while Snyk Code provides SAST, visibility, prioritization, and policy controls. ### Source excerpt Secure and accelerate your adoption of AI coding with pre-screened auto-fixes and autonomous code security for modern, developer-loved SAST. [Next page]()