Artificial Intelligence (AI) tools have revolutionized the business landscape, offering unprecedented automation, efficiency, and innovation. Among these, Generative AI (GenAI) has gained particular traction for its ability to produce creative content, write code, and assist in decision-making. When integrated into SaaS applications, these tools can transform business operations. However, with this rapid adoption comes significant generative AI security risks, especially as organizations struggle to manage and secure these tools effectively.
NOTE: A slightly different version of this article first appeared in Forbes in July 2024 and can be read here.
The Double-Edged Sword of GenAI in SaaS
The widespread integration of GenAI tools with popular SaaS platforms like Microsoft 365, Google Workspace, and Salesforce presents a complex security challenge. According to the 2024 State of SaaS Security Report, 50% of security leaders have flagged GenAI governance as a critical SaaS security concern. The promise of automation and productivity through GenAI must be balanced against the significant risk these tools introduce.
While platforms like OpenAI’s ChatGPT offer immense utility, they often require extensive access to sensitive data within SaaS environments to function effectively. Without stringent oversight, this opens the door to potential data breaches, privacy violations, and unsanctioned access. That oversight, however, is not always so simple when it comes to SaaS security. One of the key challenges in managing the risks posed by SaaS-to-SaaS integrations, including GenAI tools, is the distributed ownership of SaaS applications across different business units. For instance, Salesforce may be managed by sales operations, outside of the direct control of IT and security teams. This decentralized ownership limits the visibility security teams have over these applications, making it difficult to track, assess, and remediate integration risks effectively.
What Is Shadow AI in SaaS?
Shadow AI refers to the adoption and use of AI tools by employees without formal IT or security approval. This unsanctioned use of GenAI tools within SaaS applications can create blind spots for security teams, leading to unmonitored data access and the risk of exposing sensitive information. With the rapid growth of these tools, especially free trials or low-barrier integrations, the presence of Shadow AI in SaaS environments is on the rise. Security teams must address this growing risk to prevent data leakage and maintain control over the organization’s SaaS security posture.
Top 5 Security Concerns with GenAI in SaaS
- Unsanctioned Use (Shadow AI) - A recent survey by The Conference Board found that 56% of US employees already use GenAI tools at work, often without IT or security oversight, creating visibility and control gaps. Free trials and readily available integrations can entice business users to adopt GenAI tools without proper oversight.
- Wide Access to Data - GenAI tools often require access to a broad range of data within SaaS environments, increasing the risk of exposure. According to the 2024 State of SaaS Security Report, 33% of SaaS integrations are granted sensitive data access or privileges to the core SaaS application. This broad and often unrestricted access raises the potential for data breaches and unauthorized access to sensitive information within platforms like Zoom recordings, instant messaging in Slack, or sales pipeline and customer data in Salesforce.
- Privacy Violations: Many GenAI tools collect user data for training purposes. Organizations could inadvertently expose their data or violate regulations like GDPR or CCPA if they don't carefully scrutinize the privacy policies and data usage terms of GenAI tools. More concerning, GenAI models can inadvertently leak sensitive information during outputs, compromising confidentiality..
- Lack of Transparency: Understanding how GenAI tools operate and make decisions can be challenging. This lack of transparency makes it difficult for security teams to identify and mitigate potential security risks.
- Business User Risks: While leveraging GenAI's potential, business users might overlook security considerations. This can happen during integration with core SaaS applications. Critical security decisions, like the level of data access granted to the GenAI tool or reporting the integration to IT, can be missed during this process, increasing security risks.
Governing GenAI in SaaS: Key Strategies
To address these risks, security teams must take proactive steps:
- Create a GenAI Security Policy: Define clear policies for generative AI security and adoption, including guidelines for data access, tool approval, and employee training.
- Centralized Visibility: Use a SaaS Security Posture Management (SSPM) platform to gain visibility into all GenAI integrations and manage their data access.
- Enforce Least Privilege Access: Apply the principle of least privilege to limit the data that GenAI tools can access.
- User Education: Educate employees on the risks of unsanctioned GenAI tools and best practices for safe integration.
- Continuous Monitoring: Stay updated on emerging GenAI trends and regularly assess the security of your GenAI-integrated SaaS environment.
How Valence Security Helps Manage GenAI Risks in SaaS
As the use of GenAI tools in SaaS applications grows, so too does the need for robust security controls. Valence offers a comprehensive SaaS Security platform for identifying and managing risks associated with both sanctioned and unsanctioned (Shadow AI) GenAI tools. Our platform provides deep visibility into GenAI integrations within your SaaS ecosystem, helping you uncover hidden tools that could expose sensitive data or violate internal policies.
Valence’s SSPM capabilities ensure you have centralized oversight of all SaaS-to-SaaS integrations, including GenAI tools, and enable you to enforce the principle of least privilege by managing access controls. For instance, Valence's detection capabilities can uncover GenAI tools that may have excessive access to emails, calendars, or even customer data. The platform's GenAI mapping filters reveal how these integrations are using sensitive data, allowing security teams to swiftly mitigate risks.
By analyzing factors like data access permissions and the functionalities of the tool, Valence helps prioritize remediation efforts and focus on the integrations posing the highest security risk. In addition, Valence helps security teams to identify recently unused GenAI integrations, which can be a signal that they are no longer active and can (and should) be revoked. For example, the dormant integration may have been set up by a former employee of the organization, but revoking those integrations / OAuth tokens was not part of the employee offboarding process. These overlooked integrations can continue to provide access, posing significant security risks if not properly addressed.
Remember the challenge of distributed ownership of SaaS mentioned earlier? By offering Role-Based Access Control (RBAC) for non-security SaaS administrators and fostering collaboration with business users, Valence ensures that security oversight extends across all business units. With Valence, security teams can gain centralized visibility and control over all SaaS integrations, ensuring that even those managed outside traditional IT boundaries remain secure. This centralized management is particularly critical for identifying and managing the risks posed by unsanctioned or dormant GenAI tools that could otherwise slip through the cracks.
By working closely with SaaS admins and business users, Valence facilitates context-driven risk assessments to ensure GenAI tools are used securely across the organization. Valence provides both guided and automated SaaS risk remediation, including the ability to automatically communicate with business users to clarify if there is a necessary reason for the integrations.
What Is The Future of Generative AI in Cybersecurity?
Of course, discussion of GenAI adoption and governance extends beyond SaaS applications. As Generative AI continues to evolve, so too will its role in cybersecurity. While the automation capabilities of GenAI tools offer promising opportunities for threat detection and response, they also open new attack vectors for cybercriminals. The challenge will lie in balancing innovation with generative AI security measures to ensure these tools are leveraged safely. AI-driven attacks, such as phishing schemes generated by GenAI, could become more sophisticated, making it essential for security teams to stay ahead of emerging threats. Ensuring secure and compliant usage of GenAI tools will be a central focus as we move into the future of cybersecurity.
Uncover Hidden GenAI Risks with Valence
Valence provides unparalleled insights into Shadow AI and SaaS risks related to GenAI tools, empowering security teams to regain control over GenAI tools and protect sensitive data. Our solution identifies risky integrations, helps monitor data access, and ensures that your organization's SaaS security aligns with internal policies and regulatory standards.
Take control of your SaaS environment and protect against the rising tide of Shadow AI and GenAI risks. Schedule a demo today to learn how Valence can help secure your SaaS applications.
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