The Rise of Shadow AI: Is Your Organization Vulnerable from the Inside?
Shadow AI often enters the workplace unnoticed, as employees rely on generative AI to handle emails, documents, and even coding challenges. What they don’t always realize is that these tools, often accessed through personal accounts or unsanctioned browser extensions, can introduce new and invisible risk vectors that attackers may exploit.
In many organizations, the absence of controls around generative AI means sensitive data is processed outside governance channels, increasing the risk of compliance and operational blind spots.
A growing attack surface from within
Shadow AI is expanding the threat landscape in three ways:
- Data leakage through prompts: Employees sometimes unknowingly share sensitive business data with AI tools. While some AI providers state they do not use customer prompts for training, concerns remain around data retention and potential exposure through third-party plugins.
- Bypassing security controls: Many public AI services run on infrastructure outside the organization’s control. Without visibility or access policies, these tools create unmanaged communication channels beyond the reach of perimeter defenses.
- Obfuscation of malicious behavior: Attackers could attempt to disguise phishing or escalation attempts as AI-related activity. Internal misuse makes it harder to distinguish between user error and malicious intent.
Why Traditional Security Policies Fail Against Shadow AI
Conventional policies assume visibility. But when tools operate outside managed infrastructure, that assumption breaks down. Browser extensions, personal chatbots, and public APIs bypass perimeter controls and disappear into encrypted traffic.
A recent Forbes article found that while 75% of CISOs are concerned about shadow AI, only 26% have any visibility into how often or where these tools are used. Traffic logs might show a connection to chat.openai.com, but not the content of submitted prompts. Without prompt visibility, forensics and accountability both fail.
Bringing visibility and control into balance
Solving shadow AI requires combining detection with usable safeguards. When secure options aren’t provided, users reach for unvetted ones. Instead, we focus on making sanctioned tools easier to use – and unsafe behaviors easier to detect.
Discovering Actual Shadow AI Usage in Your Organization
Network telemetry such as DNS and proxy logs can help uncover AI tool usage across the organization. In many environments, this reveals shadow AI activity spanning teams like Marketing, HR, Finance, and Engineering alongside Development.
Monitoring behavioral baselines
Our partnership with Darktrace allows CBTW clients to gain behavioral insights across the network. Darktrace models normal activity across users and endpoints and flags anomalies such as unusual data transfers that may indicate use of unmanaged AI platforms, even when these bypass traditional perimeter defenses.
Governance for a safe AI environment
Organizations are increasingly complementing perimeter defenses with embedded governance practices tailored for AI use. That means:
- Clear policies for AI use tied to business roles
- Prompt logging for enterprise LLMs where supported
- Awareness campaigns tied to AI-enabled phishing tactics
- Approval workflows for new tool adoption
- Context-aware access management
For a cloud-based cardiac platform, CBTW implemented identity governance controls to help manage user and partner access across the organization’s cloud environment. These controls supported the platform’s efforts to meet SOC 2 compliance requirements by aligning access management with data handling policies and approval workflows.
The next frontier of insider risk
Security teams are progressively recognizing that threats don’t only come from malware but also from unmonitored AI use, unmanaged prompts, and the growing challenge of shadow AI. Addressing these risks requires new detection and governance approaches.
At CBTW, we help organizations identify and manage these hidden vulnerabilities through AI-driven monitoring, targeted red teaming, and partnerships with leaders like Darktrace. Together, we enable clients to stay ahead of insider risks in the generative AI era while balancing security with innovation.
