How to Secure a Development Environment

Still think your CI/CD pipeline is safe? Time to wake up! DevOps teams prioritize speed. Ship fast. Deploy often. Automate everything. But here’s the truth nobody wants to hear: Your pipeline is a direct line to production — and attackers know it. Why is it risky? • CI/CD tools (like Jenkins, GitLab, GitHub Actions) often hold secrets, SSH keys, cloud creds • Pipelines run with high privileges – often root, often unrestricted • A single vulnerable script or exposed token can lead to full compromise • Logs, artifact registries, and container images = goldmine for attackers • And guess what? Security is still an afterthought in too many teams What can you do to protect it? • Shift Left on Security – Integrate SAST/DAST/IaC scanning in every build – Fail builds on critical CVEs • Use Secrets Management – Stop hardcoding secrets in repos or pipeline variables – Use tools like Vault, AWS Secrets Manager, Doppler… • Implement Least Privilege in Your Pipelines – Don’t let pipelines deploy as root if they don’t need to – Use scoped service accounts, not blanket permissions • Connect Your Pipelines to the SOC – Feed CI/CD logs into your SIEM – Alert on anomalous build triggers, privilege escalation, or credential usage • Secure Your Build Agents & Containers – Harden runner environments – Don’t reuse agents across projects or tenants – Scan containers before pushing to registry Your pipeline isn’t just a toolchain — it’s your production supply line. Treat it like critical infrastructure. Secure it. Monitor it. Lock it down. #DevSecOps #CI_CD #SOC #Cybersecurity #ShiftLeft #DevOpsSecurity #SupplyChainSecurity

Day 9 of MCP Security: Top 9 dev checklist items to build secure MCP Servers- 1. Structure and sanitize all user input before adding to prompts → Avoid direct string interpolation. Use templating and clearly defined variables. 2. Register only essential tools and enforce tool-level access → No generic "call-anything" agents. Tools must be explicit, minimal, and reviewed. 3. Treat system prompts like code: versioned, reviewed, auditable → Store in Git. Require PRs. A one-line prompt change can cause a full policy failure. 4. Log full agent context and decisions: prompt → context → tool → output → This is your only audit trail. Without it, you’re blind during incidents. 5. Write automated prompt tests in CI (edge cases, malicious inputs, reasoning traps) → Prompt failures are business logic failures. Catch them before prod. 6. Scrub sensitive data from injected context and agent memory → No tokens, PII, internal notes. Memory must be minimal and expirable. 7. Gate high-impact actions with review or confidence thresholds → No auto-refunds, mass updates, or API writes without safety logic. 8. Default to inaction when the model is uncertain or underinformed → Build the "safe failure" path - defer to human, escalate, or log-and-stop. 9. Disable unused tools and unexposed APIs by default → Every tool the agent can “see” is a surface. Keep tool registration lean and explicit. No unvetted access.

This blog post, "Secure Vibe Coding Guide," published by the Cloud Security Alliance in April 2025 and authored by Ken Huang, CISSP, aims to elevate the practice of "Vibe Coding" by embedding a security-first mindset from its inception. Read the full "Secure Vibe Coding Guide" here: https://lnkd.in/g_thmryW * * * What is Vibe Coding? It's an AI-assisted programming approach where users describe software requirements in natural language, and LLMs generate the code. This shifts the developer's role to guiding, testing, and refining AI output. While accessible to non-programmers, it often involves accepting code without full implementation understanding, raising reliability concerns. Why is Security Crucial? Research, like that behind BaxBench, shows that top foundational LLMs can generate at least 36% insecure code. This guide bridges that gap, ensuring innovative projects are also secure. What to do? To secure "vibe-coded" applications, a holistic approach is vital. It begins with secure coding fundamentals, like avoiding hardcoded sensitive data and rigorously validating all inputs to prevent injection attacks. Next, application security (AppSec) integrates security throughout the development pipeline, with automated vulnerability scanning in CI/CD and regular penetration testing. This ensures continuous vigilance. API and GitHub security are crucial for protecting your application's entry points and codebase. Implement strong authentication for APIs, use rate limiting, and secure your repositories with 2FA and dependency updates. Database security is paramount for data protection, requiring parameterized queries to prevent SQL injection, encryption for sensitive data, and strict access controls. Crucially, AI-specific risks, as highlighted by the OWASP LLM Top 10, must be addressed. This includes defending against prompt injection, sensitive information disclosure, and supply chain vulnerabilities unique to LLMs. Finally, secure cloud deployment (leveraging platform features like firewalls and secure environment variables) and the human element (staying informed and seeking expert advice) complete the security framework, ensuring your vibe-coded innovations are robust and protected. The guide further empowers developers by including practical secure vibe coding prompts, designed to integrate security considerations directly into the AI-assisted workflow from the outset. * * * As Ken Huang, CISSP emphasizes in his "Secure Vibe Coding Guide," while vibe coding is here to stay and transforming software development, security isn't a one-time fix - it's a shared and continuous responsibility. By implementing these practices, we can build secure, reliable, and innovative applications. A huge thanks to my incredible colleague and go-to AI expert, Ben Prescott, Head of AI Solutioning at Trace3, for sharing this!

Just ship it! Test in production.... It'll be ok! Shipping secure software at high velocity is a challenge that many smaller, fast-paced, tech-forward companies face. When you're building and deploying your own software in-house, every day counts, and often, the time between development and release can feel like it's shrinking. In my experience working in these environments, balancing speed and security requires a more dynamic approach that often ends up with things happening in parallel. One key area where I've seen significant success is through the use of automated security testing within the Continuous Integration and Continuous Development (CICD) pipelines. Essentially, this means that every time developers push new code, security checks are built right into the process, running automatically. This gives a baseline level of confidence that the code is free from known issues before it even reaches production. Automated tools can scan for common vulnerabilities, ensuring that security testing isn’t an afterthought but an integral part of the development lifecycle. This approach can identify and resolve potential problems early on, while still moving quickly. Another great tool in the arsenal is the Software Bill of Materials (SBOM). Think of it like an ingredient list for the software. In fast-paced environments, it's common to reuse code, pull in external libraries, or leverage open-source solutions to speed up development. While this helps accelerate delivery, it can also introduces risks. The SBOM helps track all the components that go into software, so teams know exactly what they’re working with. If a vulnerability is discovered in an external library, teams can quickly identify whether they’re using that component and take action before it becomes a problem. Finally, access control and code integrity monitoring play a vital role in ensuring that code is not just shipping fast, but shipping securely. Not every developer should have access to every piece of code, and this isn’t just about preventing malicious behavior—it's about protecting the integrity of the system. Segregation of duties between teams allows us to set appropriate guardrails, limiting access where necessary and ensuring that changes are reviewed by the right people before being merged. Having checks and balances in place keeps the code clean and reduces the risk of unauthorized changes making their way into production. What I’ve learned over the years is that shipping secure software at high speed requires security to be baked into the process, not bolted on at the end (says every security person ever). With automated testing, clear visibility into what goes into your software, and a structured approach to access control, you can maintain the velocity of your team while still keeping security front and center. #founders #startup #devops #cicd #sbom #iam #cybersecurity #security #ciso

A bonus post this week - 🥳 Here's another great example of how AI is reshaping and expanding the role of CISOs, especially within the supply chain and critical infrastructure sectors. LLMs like ChatGPT, CodeWhisperer, and others are hallucinating non-existent packages when generating code. Attackers are now registering those fake packages (aka “slopsquatting," what a fun name, eh?) to deliver malware into real development pipelines. It's a mistake to think of "slopsquatting" as a DevSecOps issue. Developers may be the ones pulling packages, but CISOs are ultimately responsible for identifying the enterprise exposure, making recommendations to control / reduce the risk, and will be called to question as to why more wasn’t done to realize, and mitigate this risk if something happens. [Ahh...the life of the modern CISO...] According to an article in SecurityWeek (link in the comments) researchers found over 205,000 hallucinated packages from 16 models. Some open-source LLMs had hallucination rates above 20%. That’s not fringe. That’s mainstream. So what can a CISO do about it? Some quick recommendations: - Mandate an Internal Mirror for Package Repos Enforce use of internal mirrors or package proxies. These allow your security team to whitelist vetted dependencies and block packages not explicitly reviewed, even if hallucinated ones are published upstream. - Implement Rigorous Dependency Validation Establish protocols to verify the authenticity of all third-party packages, particularly those suggested by AI tools. It's not enough to "set it and forget it" with AI. It may be a fast team member, but that doesn't mean it’s always the most reliable or competent. When possible, utilize tools that cross-reference packages against trusted repositories to detect anomalies. - Improve (start) and Specify Your Developer Training Educate development teams about the risks associated with AI-generated code and the importance of scrutinizing suggested dependencies. Encourage a culture of skepticism and verification. -  Integrate LLM-Aware SCA and SBOM Enforcement Update your SCA tools and SBOM policies to flag new, low-trust, or previously unseen packages. This helps to catch LLM-influenced packages with low install counts or no public audit trail before they become production vulnerabilities. - Issue Secure Coding Guidelines for LLM-Generated Code Publish and stringently enforce internal guidance on using LLMs for code generation - including requirements for validating any dependencies suggested by AI tools. Make this part of your SDLC and annual developer training. Periodically audit for compliance when able. There is no "annual review" luxury in the age of AI-powered threats. As always, I welcome any additional insights or suggestions on how CISOs can be more proactive and empowered in reducing supply chain vulnerabilities. Thoughts? Comments?

🛑 Strengthening Security for Open Source Projects on GitHub 🛑 Open source security has become a priority for industries and governments, with regulations such as the US EO 14028 on cybersecurity, the EU Cyber Resilience Act (CRA), and other global efforts placing increased responsibility on maintainers & organizations to secure the software supply chain. Whether managing a small repo or a large GH org, you must take proactive steps to secure your codebases and protect your users, contributors, and ecosystem. ✅ To help with that, here’s a checklist of key security best practices that you can implement for GH-based projects: Identity and Access Management ☑️ Enforce 2FA for all org members & collaborators ☑️ Use GH's role-based access controls ☑️ Regularly audit team and member access to repositories Code Change Management ☑️ Enable branch protection rules ☑️ Use CODEOWNERS to assign reviewers for specific files or directories ☑️ Mandate signed commits using GPG or GH's verified commit signing Security During Development ☑️ Implement structured code reviews emphasizing security hygiene ☑️ Integrate GH advanced security tools (code scanning, secret scanning for credential leaks, dependabot for automated dependency updates, and vulnerability alerts) ☑️ Use the GH Advisory Database to inform dependency choices ☑️ Complement with 3rd party tools for deeper or language-specific analysis CI/CD Security: Secure GH Actions workflows by ☑️ Pinning action versions ☑️ Using permissions blocks to minimize token access ☑️ Avoiding untrusted PRs from running with secrets ☑️ Setting up ephemeral environments and ensuring artifact integrity ☑️ Monitor CI/CD pipelines as part of your attack surface Policies & Process ☑️ Publish a SECURITY .md file, include vulnerability disclosure policy & contact details ☑️ Setup a point of contact for triaging & fixing reported vulnerabilities ☑️ Use GH Security Advisories to privately coordinate fixes and publish transparent disclosures Open Source Maturity & Benchmarking ☑️ Achieve the OpenSSF Best Practices Badge https://lnkd.in/dNZ-DAjX ☑️ Run OpenSSF Scorecard https://lnkd.in/dy4DGVeK ☑️ Track progress over time using Scorecard metrics and GH Insights People & Education ☑️ Provide security training for contributors & maintainers ☑️ Use tools like Allstar to enforce security policies across your org 📕 Download ebook: "Recommended Practices for Hosting and Managing Open Source Projects on GitHub": https://lnkd.in/djf5729z. 📣 Security is a shared responsibility. The tools exist, the standards are emerging, and the open source community is better equipped than ever to defend itself. Every open source project is part of someone’s software supply chain. Acting with transparency and adopting layered security practices is part of maintaining that trust. #OSPO #OpenSource #Security The Linux Foundation Linux Foundation Japan Linux Foundation Europe OpenChain Project SPDX SBOM OpenSSF

Zero Trust Agile Zero Trust (ZT) is a security mindset that assumes no user, device, or system is to be trusted by default, even if inside the network. Instead of granting broad access based on location or credentials, ZT continuously verifies identity, context, and behavior before allowing access to systems, data, or code. ZT applies to Agile teams in two ways: in development (securing the people, processes, and tools used to build software) and in the product (protecting users and data). Agile teams move fast, but without strong security, they may expose sensitive data, development pipelines, or customers to cyber threats. Zero Trust in Development Agile teams work in distributed environments and use cloud-based tools. Traditional security models assume internal networks are safe. ZT doesn’t. Every access request, whether from a developer, an automation script, or a third-party integration, is verified. An unsecured pipeline can introduce vulnerabilities. ZT prevents unauthorized code changes by enforcing strict identity verification for developers pushing code, role-based access control (RBAC) to limit who can modify repositories, and cryptographic verification so only trusted artifacts reach production. Agile developers work across devices and locations. MFA and device posture checks verify that only trusted users and devices access development tools. Just-in-time access grants privileges temporarily. Data encryption protects code and credentials, even if a device is compromised. Agile teams use open-source libraries and third-party tools, which can introduce supply-chain risks. ZT mitigates them with automated dependency scanning, cryptographic verification, and continuous monitoring of integrations. Zero Trust in the Product Security doesn’t stop at development. The product itself must enforce ZT principles to protect customers, data, and integrations. A ZT product never assumes users are who they claim to be. It enforces strong authentication using MFA and passwordless login, continuous verification that checks behavior for anomalies, and granular role-based access so users only access what they need. APIs and microservices are attack vectors. ZT requires that even internal services authenticate and validate requests. API authentication and authorization use OAuth, JWT, and mutual TLS. Rate limiting and anomaly detection prevent abuse. Encryption of data in transit and at rest keeps intercepted data unreadable. ZT means each system, user, and process has the least privilege necessary. Session-based access controls dynamically revalidate permissions. End-to-end encryption secures data, even if intercepted. Data masking and tokenization protect sensitive information. Double Zero Agile teams can’t just build software fast, they have to build it securely. Embedding ZT in development means only the right people, processes, and tools can modify code. Embedding ZT in the product means the software itself protects users and data.

API Security: 16 Critical Practices You Need to Know Drawing from OWASP guidelines, industry standards, and enterprise security frameworks, here are 16 critical API security practices that every development team should implement: 1. Authentication Your first line of defense. Implement OAuth 2.0, JWT, and enforce MFA where possible. 2. Authorization RBAC and ABAC aren't buzzwords - they're essential. Implement granular access controls. 3. Rate Limiting Had an API taken down by a simple script? Rate limiting isn't optional anymore. 4. Input Validation Every parameter is a potential attack vector. Validate, sanitize, and verify - always. 5. Encryption TLS is just the beginning. Think end-to-end encryption and robust key management. 6. Error Handling Generic errors for users, detailed logs for systems. Never expose internals. 7. Logging & Monitoring You can't protect what you can't see. Implement comprehensive audit trails. 8. Security Headers CORS, CSP, HSTS - these headers are your API's immune system. 9. Token Expiry Long-lived tokens are ticking time bombs. Implement proper rotation and expiry. 10. IP Whitelisting Know who's knocking. Implement IP-based access controls where appropriate. 11. Web Application Firewall Your shield against common attack patterns. Configure and monitor actively. 12. API Versioning Security evolves. Your API versioning strategy should account for security patches. 13. Secure Dependencies Your API is only as secure as its weakest dependency. Audit regularly. 14. Intrusion Detection Real-time threat detection isn't luxury - it's necessity. 15. Security Standards Don't reinvent security. Follow established standards and frameworks. 16. Data Redaction Not all data should be visible. Implement robust redaction policies. The key lesson? These aren't independent practices - they form an interconnected security mesh. Miss one, and you might compromise the entire system. What's your experience with these practices? Which ones have you found most challenging to implement?