Cloud Security Mitigation Strategies

NSA Releases Top Ten Cloud Security Mitigation Strategies “Unfortunately, the aggregation of critical data makes cloud services an attractive target for adversaries.  This series provides foundational advice every cloud customer should follow to ensure they don’t become a victim.” ~ Rob Joyce, NSA’s Director of Cybersecurity The ten strategies are covered in the following reports 1. Uphold the cloud shared responsibility model 2. Use secure cloud identity and access management practices 3. Use secure cloud key management practices 4. Implement network segmentation and encryption in cloud environments 5. Secure data in the cloud 6. Defending continuous integration/continuous delivery environments 7. Enforce secure automated deployment practices through infrastructure as code 8. Account for complexities introduced by hybrid cloud and multi-cloud environments 9. Mitigate risks from managed service providers in cloud environments 10. Manage cloud logs for effective threat hunting Full article with each strategy report in the comment 👇🏾 #cybersecurity #cloudsecurity #cloudsec

Big Three (AWS, Azure, Google Cloud) consolidating control over security, data, and AI, I’d build a multi-layered security plan that assumes: 1. Cloud providers are not trustworthy. 2. AI-driven security enforcement will be used to restrict access to data. 3. Companies must take back control of their infrastructure or risk losing everything. Ultimate Security Plan to Prevent a Cloud Takeover 1. Infrastructure Control – Get Off Their Grid Hybrid or On-Prem Strategy: Companies must move critical IP and customer data off the Big Three’s cloud. Decentralized Compute & Storage: Leverage self-hosted AI models instead of API-based LLMs. Use alternative cloud providers (e.g., Linode, DigitalOcean, Vultr) for redundancy. Implement private storage solutions (e.g., MinIO, Ceph) to avoid S3 dependency. Data Fragmentation: Encrypt and distribute sensitive data across multiple storage locations, so no single provider has the full picture. 2. Security at the Data Layer – Assume They’ll Try to Take It End-to-End Encryption (E2EE): Encrypt data before it touches cloud storage—providers should only see ciphertext. Use self-hosted key management systems (KMS) instead of AWS/Azure KMS. Zero Trust Data Architecture: No cloud provider gets full access—data is split, sharded, and stored separately. Confidential computing (e.g., Intel SGX, AMD SEV) they can’t decrypt anything. Automated Data Poisoning Defense: Implement honeypots and monitor to detect if AI is being trained on data w/out permission. 3. AI Security – Prevent LLM Takeover Self-Hosted LLMs: Train- run proprietary AI models in-house avoid dependency on OpenAI, Google, AWS models. Poison Their Models: Deploy decoy data that triggers hallucinations in unauthorized AI training attempts. Identify patterns in data scraping attempts and dynamically alter responses. Red Team Their AI If AI security policies are being enforced against you, develop adversarial attacks to force model errors and expose flaws in their enforcement. 4. Operational Security (OpSec) – No Easy Entry Points Network Segmentation & Isolation: Treat cloud infrastructure as a hostile environment and limit cloud-to-internal connections. Air-Gapped Backups: Maintain offline, physically secured copies of critical data in case of cloud lockout. Multi-Cloud Obfuscation: Deploy services across multiple cloud providers with rotating endpoints to prevent surveillance and shutdowns. 5. Legal & Strategic Countermeasures Regulatory Pressure: Push for laws that force cloud providers to separate AI enforcement from cloud security. Public Exposure: Document and expose cloud misconfigurations and breaches to prove they are unfit to control security. Economic Leverage: Encourage mass exodus from centralized cloud providers—they’ll only stop if their revenue is threatened. Don’t Play Defense—Go on the Offensive The strategy isn’t just about protecting data—it’s about breaking Big Tech’s monopoly before they enforce total control.

10 critical actions listed in #CloudSecurityPlaybook Vol 2 by the United States Department of Defense 𝘗𝘶𝘣𝘭𝘪𝘴𝘩𝘦𝘥 𝘍𝘦𝘣 2025 1. Secure CI/CD Pipelines — Embed security into every phase: use SBOMs, SCA, GitOps, identity federation, and SAST/DAST to harden your DevSecOps lifecycle. 2. Mitigate Pipeline Threats — Follow OWASP CI/CD Top 10: restrict secrets, validate dependencies, isolate environments, and control access tightly. 3. Supply Chain Security — Vet all third-party code, generate SBOMs, and use secure artifact repositories to reduce exposure from compromised components. 4. API Security — APIs are top targets. Use gateways, enforce auth/z, rate limits, and address OWASP API Top 10 vulnerabilities. 5. Zero Trust (ZT) — Assume breach. Apply least-privilege, context-based access controls across users, devices, and workloads. 6. Use cATO — Achieve Continuous ATO for faster cloud deployment with built-in security compliance and risk monitoring. 7. Harden Containers — Use immutable, OCI-compliant containers. Apply STIGs and NIST 800-190 to secure images and runtimes. 8. Sidecar or Ambient Mesh — Choose SSCs or ambient mesh to enforce network and runtime controls with minimal developer burden. 9. Secure AI Systems — Protect training data, APIs, and models. Monitor AI behavior and restrict access to model assets. 10. Microservices Architecture — Use loosely coupled, stateless microservices for resilience, scalability, and security isolation.

☁️ 𝗖𝗹𝗼𝘂𝗱 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗶𝘀 𝗮 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲... Cloud security professionals face many hurdles like: • Hundreds of resource types can be created in the cloud with more introduced all the time  • Dozens of teams building resources  • Potentially hundreds or thousands of cloud accounts to manage  • An evolving threat landscape  🤔 𝗦𝗼 𝘄𝗵𝗲𝗿𝗲 𝗱𝗼 𝘄𝗲 𝗯𝗲𝗴𝗶𝗻? Here’s how I think about the problem but remember this is just the start 👀 𝗚𝗮𝗶𝗻 𝗛𝗼𝗹𝗶𝘀𝘁𝗶𝗰 𝗩𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆  • Use Cloud Security Posture Management (CSPM) tools like Wiz, CrowdStrike, or Prowler to inventory and scan your environments regularly ✅ 𝗗𝗲𝗳𝗶𝗻𝗲 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝘀 𝗮𝗻𝗱 𝗕𝘂𝗶𝗹𝗱 𝗣𝗼𝗹𝗶𝗰𝘆 𝗖𝗵𝗲𝗰𝗸𝘀 • Start with out-of-box rules from your tools • Tailor rules to your environment: modify severities, remove noise, and introduce custom rules as needed ⚠️ 𝗘𝗻𝗳𝗼𝗿𝗰𝗲 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗚𝘂𝗮𝗿𝗱𝗿𝗮𝗶𝗹𝘀 • Tools will generate a backlog of findings and remediation efforts will likely face some form of pushback or delay • By putting security guardrails in place like AWS Service Control Policies, Kyverno for Kubernetes, or code scanning, we can prevent net-new findings (e.g., misconfigurations, vulnerabilities) from being introduced in the environment 📋 𝗣𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗲 𝗮𝗻𝗱 𝗥𝗲𝗺𝗲𝗱𝗶𝗮𝘁𝗲 • Analyze findings to identify those with significant risks to your organization • Build automated remediation workflows with Cloud Custodian or similar to address existing issues at scale 🔍 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 • Regularly validate that your preventative and detective controls are working as expected 🥷 𝗔𝗱𝘃𝗲𝗿𝘀𝗮𝗿𝘆 𝗮𝗻𝗱 𝗧𝗵𝗿𝗲𝗮𝘁 𝗦𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻  • Assess your environment against common and emerging threats • Understand and simulate adversarial attacks like Privilege Escalation, Lateral Movement, and Defense Evasion • Did you detect these or is there more work to be done? ------------------------------------------------------------------------------- Like I said, it's just the tip of the iceberg... We didn’t even cover cloud-specific security configurations, secure development and deployment processes, application security, IAM, Networking, containers, etc…. 𝗪𝗵𝗮𝘁 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀 𝗼𝗿 𝘁𝗼𝗼𝗹𝘀 𝗵𝗮𝘃𝗲 𝗽𝗿𝗼𝘃𝗲𝗻 𝗲𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲 𝗶𝗻 𝗲𝗻𝗵𝗮𝗻𝗰𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗰𝗹𝗼𝘂𝗱 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆? #cloudsecurity #cloudengineering #cloud #aws #azure #gcp