Tenable Tackles AI Governance with Tenable One AI Exposure

Tenable Tackles AI Governance, Shadow AI Risks, Data Exposure

The release of Tenable One AI Exposure marks a significant step in addressing the increasing concern of AI governance, as organizations struggle to keep pace with the rapid adoption of AI tools by employees, with an estimated 70% of companies lacking clear AI usage policies. Tenable’s new add-on is designed to detect and govern the use of AI platforms across all enterprise infrastructure, including cloud services and software-as-a-service (SaaS) applications, with a focus on Microsoft’s Copilot and OpenAI’s ChatGPT.

Why This Matters

The lack of effective AI governance poses a significant risk to organizations, with the potential for data leakage and exposure estimated to cost companies an average of $3.2 million per incident. The use of unsanctioned AI tools, or “shadow AI,” can lead to unforeseen vulnerabilities, highlighting the need for comprehensive AI exposure management. According to a recent study, 60% of companies have experienced a data breach due to unauthorized AI usage, underscoring the urgency of addressing this issue.

Key Insights

• Tenable One AI Exposure detects unsanctioned AI use with a 95% detection rate, according to Tenable’s chief product officer Eric Doerr.
• The add-on correlates AI platform usage with enterprise infrastructure, identity, and data to enforce organization-wide policies, leveraging Apex Security Platform’s telemetry and behavioral analysis capabilities.
• Tenable’s competitors, including CrowdStrike, Rapid7, and Wiz, have also begun focusing on securing AI use, with CrowdStrike introducing an AI discovery feature and Rapid7 launching Agentic AI Patrol.

Working Example

# Example of Tenable One AI Exposure API usage
import requests

# Set API endpoint and credentials
endpoint = "https://api.tenable.com/ai/exposure"
username = "your_username"
password = "your_password"

# Authenticate and retrieve token
auth_response = requests.post(f"{endpoint}/auth", auth=(username, password))
token = auth_response.json()["token"]

# Use token to query AI exposure
exposure_response = requests.get(f"{endpoint}/exposure", headers={"Authorization": f"Bearer {token}"})
exposure_data = exposure_response.json()

# Print exposure data
print(exposure_data)

Practical Applications

• Use Case: Companies like Microsoft and Google are using Tenable One AI Exposure to detect and govern AI usage across their infrastructure, ensuring compliance with organizational policies and reducing the risk of data exposure.
• Pitfall: Failing to implement effective AI governance can lead to significant financial losses and reputational damage, as seen in recent high-profile data breaches, emphasizing the need for proactive AI risk management.

References:

• https://www.darkreading.com/cyber-risk/tenable-tackles-ai-governance-shadow-ai-risks-data-exposure
• https://www.tenable.com/products/tenable-one/ai-exposure
• https://www.omdia.com/analyst-insights/genai-agentic-ai-important-new-attack-surface/