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Cloud Security Alliance

SearchLeak: Copilot Data Exfiltration Exploited | CSA Zero-Trust AI Governance for Multi-Agent Systems | CSA Dangling CNAMEs: Hidden Cloud Risk | CSA Agentic Payments in Financial Services | CSA Mythos and the Future of Cybersecurity | CSA AI-Driven Cloud Risk: Defenders Lose Ground | CSA Financial Services Industry Shifts from AI Adoption to | CSA CSAI Foundation Announces RiskRubric V2 as the Next Key | CSA RiskRubric Updates: AI Risk Assessment | CSA Over 80% of Organizations that Miss 24-Hour Patch Window Report | CSA ORCHIDEAS & MAESTRO: Secure AI Design | CSA Top 6 Claude Security Risks to Watch | CSA Cloud Cost Optimization in 2026 | CSA HIPAA Rule Overhaul in 2026 | CSA AI-Driven Exploits Outsmart Detection | CSA MCP Risks CISOs Should Prepare For | CSA AI Governance for Trust and Compliance | CSA MTTP: Patch Cycles Too Slow | CSA Cloud Security Evolution: Security Teams Lead | CSA Misconfigurations Break Customer Trust in Apps | CSA Taming Shadow AI: C-Suite Strategies | CSA Agentic AI Threats: Five Powers | CSA AIUC-1: Agentic AI Governance | CSA 2026 Threat Report for CISOs | CSA Securing AI in AWS: Runtime Detection & Response | CSA SLMs, LLMs, and the DSPM Difference | CSA OT Security Timeline: Mythos and Patch Pace | CSA Blast Radius and Cloud Threat Detection | CSA State of AI Cybersecurity 2026: 92% Concerned | CSA AI in MDR for Franchise & Multi-Location Ops | CSA AI Regulation: Identity and Authorization Gap | CSA MITRE ATT&CK for Cloud: Detection Coverage Guide | CSA Shadow AI Agents: The Insider Threat | CSA Medical Device Breaches Reveal Cloud Security Gaps | CSA AISMM: AI Security Maturity Model for Cloud | CSA Globee® Awards for Artificial Intelligence (AI) Honors Cloud | CSA Patching Smarter for Mythos Security | CSA SDP v3: Identity-First Zero Trust for AI | CSA AI-Ready Security Documents Beyond STIX, OSCAL, and SARIF | CSA Penetration Testing for ISO 42001 & Trust | CSA AI Agent Posture: Data-First Security Guardrails | CSA AI Agents Go Beyond Output: Enterprise Security | CSA AI Agent Security Starts with Scope Control | CSA Identity Spoofing vs. Identity Abuse | CSA AARM: Securing the Agentic Runtime | CSA Securing the Agentic Control Plane | CSA CSAI Foundation Announces Key Milestones to Secure the Agentic | CSA Catastrophic AI Risk Controls | CSA Cloud to AI: Building Secure Programs | CSA Identity in AI Era: Zero Trust's First Pillar | CSA SDLC Visibility: Securing Multi-Cloud Development Lifecycles | CSA AI Agent Identity Is Solved Backwards | CSA 8 Truths About Cloud Privilege Risk | CSA AI Governance: Mature Programs | CSA Agent Access Management: Data-First Security | CSA Glasswing: AI-Driven Security for Safer Software | CSA Runtime Security: Detection & Real-Time Cloud | CSA Identity as the OS for AI Security | CSA Cloud Misconfigurations Drive Attacks at Scale | CSA Sensing AI Behavior with the WBSC Probe Library | CSA An Actionable Guide to GDPR Compliance for Startups | CSA Cloud Security LIVE 2026: AI Risk & Trust | CSA Shadow AI Agents: Enterprise Governance | CSA Rethinking Non-Human Identity Security | CSA New Cloud Security Alliance Survey Reveals 82% of Enterprises Have Unknown AI Agents in Their Environments More Than Half of Organizations Experience AI Agent Scope | CSA SANS Institute, Cloud Security Alliance, [un]prompted, and OWASP | CSA AI Agents Are Talking: Are You Listening? | CSA Software Supply Chain Security Needs an Upgrade Choosing the Right AI Standard: 7-Point Guide | CSA Audience-Driven Authorization for AI Agents | CSA A CISO's Guide to Cloud Security Architecture | CSA Who’s Behind That Action? 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Cloud Risk: Top 3 Threats & AI Tools | CSA
2026-04-22 · via Cloud Security Alliance

Written by Pallavi Singh, Sr. Product Marketing Manager, Darktrace.

With cloud computing, organizations are storing data like intellectual property, trade secrets, Personally Identifiable Information (PII), proprietary code and statistics, and other sensitive information in the cloud. If this data were to be accessed by malicious actors, it could incur financial loss, reputational damage, legal liabilities, and business disruption.

Last year, data breaches in solely public cloud deployments were the most expensive type of data breach, with an average of $5.17 million USD, a 13.1% increase from the year before.

So, as cloud usage continues to grow, the teams in charge of protecting these deployments must understand the associated cybersecurity risks.

What are cloud risks?

Cloud threats come in many forms, with one of the key types consisting of cloud risks. These arise from challenges in implementing and maintaining cloud infrastructure, which can expose the organization to potential damage, loss, and attacks.

There are three major types of cloud risks:

1. Misconfigurations

As organizations struggle with complex cloud environments, misconfiguration is one of the leading causes of cloud security incidents. These risks occur when cloud settings leave gaps between cloud security solutions and expose data and services to unauthorized access. If discovered by a threat actor, a misconfiguration can be exploited to allow infiltration, lateral movement, escalation, and damage.

With the scale and dynamism of cloud infrastructure and the complexity of hybrid and multi-cloud deployments, security teams face a major challenge in exerting the required visibility and control to identify misconfigurations before they are exploited.

Common causes of misconfiguration come from skill shortages, outdated practices, and manual workflows. For example, potential misconfigurations can occur around firewall zones, isolated file systems, and mount systems, which all require specialized skill to set up and diligent monitoring to maintain.

2. Identity and Access Management (IAM) failures

IAM has only increased in importance with the rise of cloud computing and remote working. It allows security teams to control which users can and cannot access sensitive data, applications, and other resources.

There are four parts to IAM: authentication, authorization, administration, and auditing and reporting. Within these, there are a lot of subcomponents as well, including but not limited to Single Sign-On (SSO), Two-Factor Authentication (2FA), Multi-Factor Authentication (MFA), and Role-Based Access Control (RBAC).

Security teams are faced with the challenge of allowing enough access for employees, contractors, vendors, and partners to complete their jobs while restricting enough to maintain security. They may struggle to track what users are doing across the cloud, apps, and on-premises servers.

When IAM is misconfigured, it increases the attack surface and can leave accounts with access to resources they do not need to perform their intended roles. This type of risk creates the possibility for threat actors or compromised accounts to gain access to sensitive company data and escalate privileges in cloud environments. It can also allow malicious insiders and users who accidentally violate data protection regulations to cause greater damage.

3. Cross-domain threats

The complexity of hybrid and cloud environments can be exploited by attacks that cross multiple domains, such as traditional network environments, identity systems, SaaS platforms, and cloud environments. These attacks are difficult to detect and mitigate, especially when a security posture is siloed or fragmented. 

Some attack types inherently involve multiple domains, like lateral movement and supply chain attacks, which target both on-premises and cloud networks. 

Challenges in securing against cross-domain threats often come from a lack of unified visibility. If a security team does not have unified visibility across the organization’s domains, gaps between various infrastructures and the teams that manage them can leave organizations vulnerable.

Adopting AI cybersecurity tools to reduce cloud risk

For security teams to defend against misconfigurations, IAM failures, and insecure APIs, they require a combination of enhanced visibility into cloud assets and architectures, better automation, and more advanced analytics. These capabilities can be achieved with AI-powered cybersecurity tools.