Vulnerability Assessment in Cloud Platforms

𝗝𝘂𝘀𝘁 𝗴𝗲𝘁𝘁𝗶𝗻𝗴 𝗶𝗻𝘁𝗼 𝗰𝗹𝗼𝘂𝗱 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆? 𝗧𝗵𝗲 𝗼𝗳𝗳𝗲𝗻𝘀𝗶𝘃𝗲 𝘀𝗶𝗱𝗲 𝗼𝗳 𝗶𝘁… One of the most important parts of offensive cloud security is enumeration understanding what's exposed, what's misconfigured, and where the doors are left open. 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝘁𝗵𝗲 𝘁𝗼𝗼𝗹𝘀 𝗜 𝘄𝗶𝘀𝗵 𝘀𝗼𝗺𝗲𝗼𝗻𝗲 𝗵𝗮𝗱 𝗽𝗼𝗶𝗻𝘁𝗲𝗱 𝗺𝗲 𝘁𝗼 𝗲𝗮𝗿𝗹𝗶𝗲𝗿 👇 ☁️ 𝗔𝗪𝗦 → AWS CLI — enumerate IAM roles, S3 buckets, EC2 instances, and more before touching any third-party tool. → Pacu — open-source AWS exploitation framework. Think Metasploit, but cloud-native. → S3Scanner — quickly finds open S3 buckets you didn't know were exposed. ☁️ 𝗚𝗖𝗣 → gcloud & gsutil — don't overlook the default SDK. List projects, enumerate IAM bindings, inspect storage buckets incredibly powerful for recon. ☁️ 𝗔𝘇𝘂𝗿𝗲 → Azure CLI (az) — enumerate subscriptions, resource groups, role assignments, and managed identities straight from the terminal. ☁️ 𝗠𝘂𝗹𝘁𝗶-𝗰𝗹𝗼𝘂𝗱 → ScoutSuite — audits AWS, Azure, GCP, Alibaba Cloud & OCI for misconfigurations. Great first stop. → Prowler — security benchmarking across AWS, GCP & Azure. CLI-based and beginner-friendly. → PurplePanda — maps privilege escalation paths within and across cloud environments & SaaS. → TruffleHog — scans for exposed secrets and credentials hiding in code repos and cloud storage. → Nuclei — fast, template-based scanner great for cloud-exposed attack surfaces. → Wiz — Cloud security platform that provides deep visibility into misconfigurations, toxic combinations, and attack paths across environments. Great for understanding real-world risk in context. Honest take: you don't need to master all of these at once. Pick one cloud provider, set up a free lab environment (AWS free tier is a great start), and just start poking around. Some learning resources; 🟡 AWSGoat: AWSGoat is a vulnerable by design AWS infrastructure featuring OWASP Top 10 web application security risks (2021) and AWS service based misconfigurations. - https://lnkd.in/ewZvYp7A 🟡 Pwned Labs: Free hosted labs for learning cloud security. - https://pwnedlabs.io/ 🟡 Hacktricks - https://lnkd.in/eUnsj7vZ 🟡 Awesome Cloud security https://lnkd.in/eEcnmXa2 The best way to learn offensive cloud security is by doing not just reading. What tools are you using to get started? Drop them below 𝗟𝗲𝘁’𝘀 𝗥𝗲𝗽𝗼𝘀𝘁 𝗳𝗼𝗿 𝗼𝘁𝗵𝗲𝗿𝘀 𝘁𝗼 𝗹𝗲𝗮𝗿𝗻 ♻️ 𝗔𝗻𝗱 𝗮𝘀 𝗮𝗹𝘄𝗮𝘆𝘀, 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗻𝗲𝘃𝗲𝗿 𝗲𝗻𝗱𝘀.

Dear Business & IT Audit Leaders, Cloud environments are not inherently secure. They are only as resilient as the questions we ask. As a cybersecurity audit leader, I don’t begin any cloud assessment without interrogating the architecture through 8 critical dimensions. These aren’t just technical checks, they’re strategic filters that reveal business risk, regulatory exposure, and operational blind spots. Whether you're migrating, auditing, or optimizing your cloud stack, these questions reveal the real posture of your environment. They cut through vendor promises and dashboards to expose what matters: risk, resilience, and regulatory readiness. Here’s the framework I use to guide CISOs, CTOs, and audit teams: 📌 Business Purpose & Data Sensitivity Every cloud asset must be mapped to its business function and data classification. If you don’t understand the value and risk of what’s hosted, you’re auditing in the dark. 📌 Cloud Service Model & Deployment Type IaaS, PaaS, SaaS, and Public, Private, Hybrid, each shift the shared responsibility model. Misidentifying this leads to control gaps and audit failures. 📌 Identity, Access & Privileged Account Management IAM policies, MFA enforcement, and least privilege aren’t optional, they’re the backbone of cloud security. I assess not just design, but operational discipline. 📌 Encryption at Rest & In Transit I validate cryptographic standards, key lifecycle management, and segregation of duties. Weak encryption is a silent breach waiting to happen. 📌 Network & Perimeter Defense Firewalls, segmentation, and intrusion prevention must be tested for effectiveness, not just existence. I look for real-world resilience, not checkbox compliance. 📌 Vulnerability Management & Threat Detection Scanning cadence, patch velocity, and incident response maturity determine whether threats are contained or compounded. I benchmark against threat intelligence and business risk. 📌 Business Continuity & Disaster Recovery Validation RTO/RPO metrics are meaningless without tested recovery capabilities. I simulate failure scenarios to assess readiness under pressure. 📌 Regulatory Compliance & Governance Frameworks From HIPAA to NIST to ISO 27001, I verify not just policy alignment but operational execution. Governance must be embedded, not just documented. These 8 dimensions form the backbone of my cloud audit methodology. They help organizations move from reactive security to proactive resilience. If you're leading cloud transformation, audit readiness, or cybersecurity strategy, this is where your assessment should begin. Let’s discuss: Which of these questions do you think is most overlooked in your organization? #CloudSecurity #CyberAudit #ITAudit #AIaudit #RiskManagement #CloudSecurityRisk #CyVerge #CloudSecurityAudit #Cyberverge #Governance #CloudResilience #CloudGovernance

Navigating CVE Vulnerabilities: Top Security Tools Safeguarding the Industry 🛡️💻 In today's hyper-connected digital landscape, Common Vulnerabilities and Exposures (CVEs) represent critical threats that can cripple organizations overnight. CVEs are standardized identifiers for publicly disclosed cybersecurity vulnerabilities, often stemming from software bugs, misconfigurations, or outdated dependencies. According to recent reports, over 20,000 CVEs were cataloged in 2024 alone, with many targeting open-source components used in enterprise systems. Ignoring them isn't an option—proactive detection and mitigation are key to robust security postures. 🚨 Industry leaders rely on a mix of proprietary and open-source tools to scan, assess, and remediate CVEs. These tools integrate into DevSecOps pipelines, enabling shift-left security where vulnerabilities are caught early. Let's spotlight some open-source gems that are game-changers: - Steampipe 📊: Transforms APIs into SQL tables for querying cloud infrastructure, uncovering misconfigs that could lead to CVEs in AWS, Azure, and more. - Syft & Grype🦉: From Anchore, Syft generates Software Bills of Materials (SBOMs) listing app dependencies, while Grype scans them for known CVEs in containers—essential for Kubernetes environments. - Opengrep ∞: A fresh fork of Semgrep, this SAST tool semantically scans code for vulnerability patterns, ensuring custom rules catch CVEs before deployment. - Prowler 🕵️♂️: Excels in multi-cloud audits, flagging CVE-exposed resources in real-time across GCP, AWS, and Azure. - OSV-Scanner 🔍: Google's vulnerability database tool scans dependencies against a vast CVE repository, prioritizing high-severity issues. - Checkov ✅: Static analysis for Infrastructure as Code (IaC), preventing CVE-prone setups in Terraform or CloudFormation. Adopting these tools fosters a culture of security-by-design, reducing breach risks and compliance headaches. Whether you're a startup or Fortune 500, start integrating them today—your cyber defenses will thank you! 🌐🔒

After a conversation with Ferenc Spala earlier this week, something struck me about how we manage risk. I think we over-index on the Common Vulnerabilities and Exposures (CVE) list, guided by CVSS scores. CVEs and CISA KEVs take up most of the mental bandwidth. While this approach helps create awareness, it also obscures a much broader set of risks that fall outside of that traditional vulnerability classification scheme. Attackers don’t stop to ask whether a system has CVEs; for them, any weak spot is an opportunity. What are these “other” risks? They run the gamut from misconfigurations to end-of-life (EOL) systems, missing or poorly maintained controls, incorrect permissions, and more. A default password left on a critical system, for example, may not show up in a CVE database, but it can be just as damaging as a high-severity software flaw. A cloud file share with world-readable permissions can be the perfect foothold for lateral movement. Historically, teams have heavily relied on CVE-based metrics to decide which vulnerabilities to patch first, often using CVSS/EPSS as the key determinant for priority. This has served the industry reasonably well in terms of tackling the most visible software flaws. But as attack surfaces become more complex, and as we integrate more services, platforms, and APIs than ever before, the risk we face isn’t limited to neatly cataloged CVEs. Ransomware operators, for example, routinely abuse misconfigurations and credential issues to pivot through environments. That’s where an expanded, more holistic view of exposure management comes in. The idea we’ve been pursuing is to map non-CVE exposures like misconfigurations or control gaps to TTPs (tactics, techniques, and procedures) that attackers employ when exploiting typical CVEs. In other words, if a certain set of TTPs is commonly used to exploit a known vulnerability in a particular software component, those same TTPs may be relevant if there’s a misconfiguration that enables the same lateral movement or privilege escalation. By analyzing both CVEs and non-CVEs through the lens of TTPs, we can prioritize remediation efforts in a much more unified and realistic way. From a defensive standpoint, the potential impact and the actual attacker workflow may look very similar even if one is assigned a CVSS score and the other isn’t. By classifying both exposures in terms of the TTPs they enable, we can see that their remediation priority might be comparable. This approach helps security teams escape the trap of “CVE-centric thinking” and pushes us to see our environment more through the eyes of an adversary. This helps us think beyond Patch Tuesday and OWSAP top 10. True potential in exposure management lies in a unified view that spans the spectrum of vulnerabilities, misconfigurations, and architectural weaknesses. I am excited about the move from patch management to genuine exposure management!! More here: https://lnkd.in/gAur4uCd

Are you prepared for the storm that may be brewing in your cloud environment?  With the right tools and strategies, you can secure your assets and fortify your defenses. Here’s your Advanced Cloud Security Audit Checklist using open-source tools:  ➡️ Cloud Resource Inventory Management   - Use CloudMapper to discover and map all cloud assets.   - Ensure accurate asset tracking for security visibility.  ➡️ IAM Configuration Analysis   - Audit IAM policies with PMapper to identify risks.   - Enforce least privilege access to minimize the attack surface.  ➡️ Data Encryption Verification   - Validate encryption protocols with OpenSSL & AWS KMS.   - Ensure data encryption at rest and in transit.  ➡️ Network Security & Vulnerability Assessment   - Scan security groups & NACLs using Scout2 or Prowler.   - Detect unintended access points and misconfigurations.  ➡️ API Security & Vulnerability Scanning   - Test API authentication with OWASP ZAP or APIsec.   - Identify API weaknesses and prevent unauthorized access.  ➡️ Cloud Penetration Testing & Vulnerability Scanning   - Continuously scan for vulnerabilities using OpenVAS or Nessus.   - Detect and remediate security flaws in cloud infrastructure.  ➡️ IaC Security Auditing   - Review Terraform & CloudFormation with Checkov.   - Detect misconfigurations before deployment.  ➡️ Logging & Cloud Activity Monitoring   - Aggregate security logs using ELK Stack or Wazuh.   - Perform anomaly detection to spot suspicious activity.  ➡️ Cloud Compliance & Regulatory Monitoring   - Automate security compliance checks with Cloud Custodian.   - Ensure adherence to GDPR, HIPAA, and SOC 2 standards.  ➡️ Audit Trail & Incident Response   - Monitor cloud logs using AWS CloudTrail or Google Audit Logs.   - Track administrative activity and detect threats early.  ➡️ MFA Enforcement & Audit   - Verify MFA settings across critical accounts.   - Enforce multi-factor authentication using MFA Checker.  ➡️ Cloud Backup & Disaster Recovery   - Perform integrity checks using Duplicity or Restic.   - Validate recovery point objectives (RPO) and test restores.  Follow Satyender Sharma for more insights !

Cloud Security Assessment It involves evaluating and ensuring the security of an organization's cloud infrastructure and services. Key components typically covered in a Cloud Security Assessment: 1. Identity and Access Management (IAM): Review and assess the effectiveness of user access controls, roles, and permissions within the cloud environment. 2. Data Encryption: Evaluate the use of encryption for data at rest, in transit, and during processing within the cloud platform. 3. Network Security: Assess network configurations, firewall rules, and traffic flow to ensure a secure and well-segmented cloud network. 4. Configuration Management: Review and validate the configurations of cloud services and resources to ensure compliance with security best practices. 5. Incident Response and Logging: Evaluate incident response plans, logging mechanisms, and the ability to monitor and respond to security incidents within the cloud environment. 6. Compliance and Governance: Ensure adherence to regulatory requirements and internal policies within the cloud infrastructure. 7. Data Loss Prevention (DLP): Assess measures in place to prevent accidental or intentional data leakage within the cloud environment. 8. Cloud Provider Security Controls: Review and validate the security controls provided by the cloud service provider (e.g., AWS, Azure, GCP). 9. Threat Intelligence Integration: Evaluate the integration of threat intelligence feeds to enhance detection and response capabilities within the cloud. 10. Container Security: Assess the security of containers and container orchestration platforms, addressing vulnerabilities and misconfigurations. 11. Serverless Security: Review security measures for serverless computing, including function-level permissions and event source security. 12. API Security: Assess the security of APIs used within the cloud environment, ensuring proper authentication and authorization. 13. Asset Inventory: Maintain an inventory of cloud assets, reviewing and validating their security configurations. 14. Supply Chain Security: Evaluate the security of third-party services and dependencies integrated into the cloud environment. 15. Continuous Monitoring and Auditing: Implement continuous monitoring and periodic auditing to detect and address security issues proactively. 16. Disaster Recovery and Business Continuity: Evaluate the cloud environment's resilience and the effectiveness of disaster recovery and business continuity plans. 17. Employee Training and Awareness: Assess the level of training and awareness among cloud users to prevent security incidents caused by human error. A comprehensive Cloud Security Assessment helps organizations identify vulnerabilities, ensure compliance, and implement measures to safeguard their cloud infrastructure and data to ensure Security posture is being improved.

𝐂𝐥𝐨𝐮𝐝 𝐀𝐈 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲: 𝐖𝐡𝐚𝐭’𝐬 𝐋𝐮𝐫𝐤𝐢𝐧𝐠 𝐁𝐞𝐧𝐞𝐚𝐭𝐡 𝐭𝐡𝐞 𝐒𝐮𝐫𝐟𝐚𝐜𝐞? A recent report from #Tenable reveals a concerning reality: nearly 𝟕𝟎% of cloud AI workloads carry at least one unremediated #vulnerability—and the rest may simply be unaudited. The widespread reliance on default, overprivileged service accounts in platforms like Google Vertex AI (used by 𝟕𝟕% of organizations) is multiplying risks across every layer of the AI stack. From misconfigured data buckets to vulnerable open-source components, attackers have more entry points than ever—and the blast radius for even minor oversights can be enormous. The infamous OpenAI Redis library incident, which exposed user data, is just one example of how simple misconfigurations can lead to major privacy breaches. Security in cloud AI isn’t just about patching bugs—it’s about adopting a risk-based, platform-wide approach. Organizations need to merge human and machine identities, enforce least-privilege access, and embed security controls directly into the MLOps pipeline. As cloud AI workloads scale, so too must our security strategies. 𝐊𝐞𝐲 𝐭𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬 𝟏. 𝐀𝐮𝐝𝐢𝐭 𝐚𝐧𝐝 𝐫𝐞𝐜𝐨𝐧𝐟𝐢𝐠𝐮𝐫𝐞 𝐝𝐞𝐟𝐚𝐮𝐥𝐭 𝐩𝐞𝐫𝐦𝐢𝐬𝐬𝐢𝐨𝐧𝐬—don’t let overprivileged accounts become your Achilles’ heel. 𝟐. 𝐀𝐝𝐨𝐩𝐭 𝐚 𝐮𝐧𝐢𝐟𝐢𝐞𝐝, 𝐫𝐢𝐬𝐤-𝐛𝐚𝐬𝐞𝐝 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡—prioritize vulnerabilities by potential impact, not just technical severity. 𝟑. 𝐄𝐦𝐛𝐞𝐝 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐢𝐧𝐭𝐨 𝐞𝐯𝐞𝐫𝐲 𝐬𝐭𝐚𝐠𝐞 𝐨𝐟 𝐲𝐨𝐮𝐫 𝐀𝐈 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞—from data ingestion to model deployment. Let’s not just innovate—let’s protect. The future of AI depends on it. Security should be at the heart of every AI initiative, not just an afterthought. 𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/gtQf-ZyG #AI #DigitalTransformation #GenerativeAI #GenAI #Innovation  #ArtificialIntelligence #ML #ThoughtLeadership #NiteshRastogiInsights 

It is quite common for me to see Azure environments where resources have been spun up without any underlying architecture, governance or security design. Maybe they started out as a temporary solution or test and suddenly became relied upon and built on top of. This opens the organization up to a lot of vulnerabilities and risk, be it from a security perspective or cost perspective... or both! Microsoft Defender for Cloud is a fantastic tool to start bringing some order to the chaos, it also has some free capabilities to get started with, see them later in this post! Here are some of the key capabilities it has to offer: AI Security Posture Management (AI-SPM): Provides granular visibility into all workloads, including AI workloads, identifying vulnerabilities across VMs, Storage Accounts, AI models, SDKs, and datasets. For example, a financial services company mitigated vulnerabilities in their AI-driven fraud detection systems using AI-SPM. Enhanced Threat Protection: Integrates with Azure OpenAI Service to protect against jailbreak attempts and data breaches. A healthcare provider used this to secure patient data in their AI diagnostic tools. Multicloud Threat Protection: Not using Azure? no problem! - This tool supports Amazon RDS and Kubernetes security, enhancing threat detection and response across AWS, Azure, and GCP. A global retailer implemented these features to secure their e-commerce platforms. Infrastructure-as-Code (IaC) Insights: Enhances security with Checkov integration, streamlining DevSecOps processes for a software development firm. Cloud Infrastructure Entitlement Management (CIEM): Optimizes permissions management, reducing attack surfaces for a tech startup. API Security Testing: Supports Bright Security and StackHawk, ensuring API security throughout the development lifecycle. A logistics company used these tools to secure sensitive shipment data. Free Capabilities Microsoft Defender for Cloud offers the foundational Cloud Security Posture Management (CSPM) capabilities for free, including continuous security assessments, security recommendations, and the Microsoft cloud security benchmark across Azure, AWS, and Google Cloud. Check out the links in the comments to learn more! #CloudSecurity #AI #MicrosoftDefender #CyberSecurity #Multicloud #CNAPP #TechNews

🔭A vulnerability was recently discovered in HTTP requests within web applications managing AWS infrastructure. These vulnerabilities could potentially allow attackers to capture access keys and session tokens (which are often temporarily shared with external users, who can upload device logs to CloudWatch), enabling unauthorized access to backend IoT endpoints and CloudWatch instances. What is at risk: 📛Attackers can intercept these credentials in clear text, potentially uploading false logs or sending MQTT messages to IoT endpoints. This not only compromises data integrity but also increases operational costs through fraudulent activities. 📞The PoC showed a peer-to-peer screen sharing application built on AWS that HTTP made requests to specific endpoints that could expose sensitive credentials. 🗒Two unique endpoints were found: ‘/createsession’ and ‘/cloudwatchupload’. When a request was sent to the ‘/createsession’, the web application responded with access keys and session tokens corresponding to an AWS IOT endpoint. These keys were successfully used to send MQTT messages to the AWS IOT endpoint. 🛠Recommended Actions: Data should be routed through an internal server that validates and securely forwards it to AWS services. Implementing centralized auditing, logging, and rate limiting will further enhance security. This case serves as a stark reminder of the ongoing risks and design flaws prevalent in integrating web applications with backend cloud services. #CyberSecurity #AWS #InfoSec #CloudSecurity #DataProtection