We're excited to introduce our monthly newsletter focused on practical tips for enhancing cloud security. In this edition, you'll find valuable insights and actionable advice to help you safeguard your cloud environment.
A comprehensive view of the evolving landscape of cloud security threats and the measures needed to address them:
- 7 top cloud security threats – and how to address them (CSO Online)
- Google Issues Cloud Security Wake-up Call as Threats Evolve (Security Boulevard)
- Confidentiality Managing Your Cloud`s Machine Identities (Security Boulevard)
- The Next Frontier in Data Security (Forbes)
- Top Threats to Cloud Computing 2024 (CSA)
Threats
- Human Errors: Common staff mistakes lead to most security incidents, creating vulnerabilities that would otherwise be covered by a strong security posture. Mistakes like leaving cloud assets unsecured or clicking on phishing links can allow threat actors to infiltrate a company's cloud environment. Regular training is essential to minimize these errors.
- Cloud-Assisted Malware: Phishing emails and malware delivery through cloud storage services are growing threats. Users should exercise caution around unsolicited emails and avoid downloading files or attachments from external sources. Strong endpoint logging capabilities and additional process-level logging are recommended.
- Data Theft: Data theft is a significant threat, especially with AI systems. Nearly a third of reported incidents are linked to data theft or leakage. This threat exposes enterprises to reputational damage, AI vulnerabilities, regulatory risks, and other dangers. Ensuring data security and integrity demands a strategic, integrated approach that combines robust security protocols, stringent access controls, and proactive threat intelligence.
- Credentials Theft: Stolen credentials are a primary attack vector. Threat actors can wreak havoc in just minutes once they've infiltrated a system. To combat credential theft, organizations should adopt a layered security approach, including strong multi-factor authentication and monitoring the dark web for stolen credentials.
- Poor Access Management: Improper access management by IT teams can lead to security gaps. Cloud environments distribute access responsibilities across multiple roles, increasing the risk of human error. Implementing strict network access controls and comprehensive security training for all personnel involved in cloud management is advised. Establishing guardrails allows teams to work within their areas while providing network security experts with necessary oversight.
- DoS and DDoS Attacks: These attacks can disrupt operations by consuming resources like bandwidth, disk space, or memory capacity. Basic cyber hygiene, robust network security, and intrusion detection systems are effective defenses. Many cloud services offer basic default protection against network flood attacks, as well as enhanced security at an additional cost.
- Data Exfiltration: Unauthorized transmission of data from the cloud can lead to significant losses. Data exfiltration can occur through the exploitation of vulnerabilities, misconfigurations, or compromised credentials. Monitoring, remediation, and legal actions are crucial to address this threat. The consequences of data exfiltration can be long-term and far-reaching, including operational disruption, downtime, lost productivity, and costs incurred to rebuild operations.
Challenges & Solutions Data security influenced by advancements in cloud technologies, the widespread adoption of software-as-a-service (SaaS) applications, and the rapid growth of generative AI are some of the evolving challenges. What to do?
- Recognize That Data Lives Everywhere: Data no longer stays in a single location. It resides within SaaS platforms like Sharepoint, Google Drive, employee laptops, collaborative workspaces like Slack, Jira, Teams, CRMs like Salesforce, HubSpot, customer support platforms like Zendesk, Intercom, on-premise file shares, and cloud platforms like AWS, Azure, and GCP. With the rise of generative AI, sensitive data is often funneled into AI-driven tools without full understanding of the implications. A holistic analysis of where data resides, how it’s transferred, and who has access is vital to ensure comprehensive security.
- Discover And Classify Data: A systematic way to discover and classify data is essential. This involves machine learning-powered solutions that continuously scan a range of data sources, including SaaS applications, cloud storage, email, endpoints, and AI integration points. Modern data discovery leverages machine learning and OCR to detect PII, PCI, PHI, and other sensitive information in unstructured documents or images and structured databases. Context-aware classification reduces false positives, providing a clear picture of data flows.
- Protect And Remediate: After identifying where sensitive data resides, the next step is to protect it and remediate existing risks. Strategies include redaction (masking critical information), labeling files with sensitivity labels, blocking unauthorized access, deleting unnecessary data, revoking access for users no longer needing it, and automating bulk remediation across applications or repositories.
- Embrace Agentless Solutions: Security solutions are shifting to agentless models, which don’t require installing software agents on every endpoint. Instead, they integrate seamlessly with existing SaaS, cloud, and AI apps. This approach shortens deployment times and makes ongoing management more efficient, especially for SaaS/cloud apps on mobile and BYOD devices.
- Don’t Overlook Generative AI Risks: Generative AI introduces risks of data leakage. Employees may unintentionally share confidential data in prompts, and AI outputs might reproduce sensitive information. Organizations must enforce usage guidelines, implement access controls, apply real-time data redaction, ensure vendor oversight, and provide employee training to leverage AI safely.
Data security in a world defined by SaaS, cloud workloads, and generative AI requires a systematic, layered approach. Continuous improvement and ongoing vigilance are crucial for effective data security, leading to greater trust, reduced risk, and a competitive edge in the marketplace