【虹科方案】AI 上線前先補洞：用「即時監控＋權限治理」把資料外洩風險壓下來

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[Hongke Insights] Plug the Gaps Before Deploying AI: Minimize Data Breach Risks with “Real-Time Monitoring + Access Control”

01. Technical Causes and Risks of AI Data Breaches

While AI enhances efficiency and improves the quality of decision-making, it often requires access to large amounts of data for training, retrieval, and inference. Without “visibility, access controls, and real-time responses,” data leaks can occur without anyone noticing.

1) Unintentional Leaks: Supply Chain Gaps and Agents Being Misled

• Supply chain risk is not an abstract concept: Mixpanel once experienced unauthorized access to its systems after an employee fell victim to an SMS phishing (smishing) attack, resulting in the leakage of some customer-identifiable information and analytics-level data; Related disclosures indicate that the data fields may include metadata such as names, email addresses, approximate locations, and browser/operating system information.
•If an AI agent is granted access to emails or documents, it may be manipulated through “indirect prompt injection”: The ShadowLeak attack demonstrated by Radware exploited hidden commands to trick ChatGPT’s Deep Research agent—which had access to Gmail—into extracting and leaking mailbox information, illustrating that “If an agent has permissions, it can potentially be exploited for malicious purposes.”

2) Data Abuse and Mismanagement: Loss of Control Over Permissions and “Over-Delegation”

When AI systems are equipped with the ability to perform actions (such as reading and writing files, querying databases, sending emails, or issuing invoices), the real risk often lies not in whether the model “will give the wrong answer,” but in whether “it can actually carry out destructive actions after giving the wrong answer.”
OWASP defines “Excessive Agency” as: a situation in which an LLM, due to having too many functions, too many permissions, or too much autonomy, is capable of performing harmful actions through unintended or manipulated outputs.

3) Compliance Risk: Fines and the Cost of Trust Are Skyrocketing Simultaneously

• Dutch regulators previously fined Experian Netherlands 2.7 million euros for GDPR violations, citing issues such as insufficient notification and other data processing problems, which underscores the strictness of enforcement in personal data governance.
• France’s CNIL imposed a total fine of 42 million euros on Free Mobile and its parent company, Free, for issues including inadequate protection of customer data. This penalty, linked to the companies’ data breach and subsequent corrective measures, demonstrates that the financial impact of a major data breach can directly reach the “operational level.”

02. How Lepide Builds a Data Leak Prevention (DLP) System for the AI Era

In response to the dynamic risks posed by “agentic” AI, we recommend a two-pronged approach: establish clear permission boundaries before deployment, and use real-time monitoring after deployment to detect anomalous behavior and address it promptly.

1) Pre-deployment governance: Start by applying the “least privilege” principle to the fullest extent possible

First, identify where sensitive data is located and who has access to it: Data classification and permission visibility at the platform level can help identify areas where data is overexposed and track permission statuses (including current permissions and changes).
Revoke "unnecessary, overly broad, or expired" permissions: The platform supports automated remediation of excessive permissions—for example, automatically revoking permissions via policies when they are no longer needed—to reduce the likelihood of "AI using human accounts as a conduit" to laterally access large amounts of confidential information.

2) Monitoring During Operation: Detect anomalies in real time and reduce exposure time

Once AI tools are deployed, static permissions are insufficient to address behavioral risks; therefore, real-time alerts and monitoring for behavioral anomalies are required—particularly in cases such as elevated account privileges, unusually high volumes of access, and sensitive operations performed during atypical time periods.
Lepide’s real-time alerts not only “notify you,” but also support rapid response actions (such as freezing accounts, rolling back operations, and isolating systems), and can be integrated with existing response workflows to maintain incident containment capabilities.

3) Integration and Automation: Turning “Discovery” into “Closed-Loop Processing”

To move beyond “detecting risks” to “preventing data breaches,” the key is to integrate alerts into existing SOC/IT processes (such as SIEM, SOAR, and ITSM) so that incidents can be prioritized, assigned, tracked, and audited.
The platform also emphasizes policy-based governance and automated remediation of excessive permissions, ensuring that permissions do not continue to expand due to personnel changes and project overlaps, and preventing AI agents from obtaining “default superuser privileges.”

In the face of the AI wave, the most prudent approach is to first “clean up” sensitive data and access controls, and then use real-time monitoring to suppress anomalous behavior as soon as it occurs.
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03. Frequently Asked Questions (FAQ) About AI Data Breaches

Q1: Why is it particularly important to prevent data leaks from generative AI?
Because generative AI is often used in workflows such as “summarizing, rewriting, comparing, and analyzing,” if the input contains personal data or trade secrets, the consequences of a data breach would extend across three areas: regulatory, financial, and trust; GDPR-related penalty cases have already demonstrated that both the intensity of regulatory enforcement and the scale of fines can be quite substantial.
Q2: How might employees unintentionally cause a data breach?
Common scenarios include: pasting unanonymized lists or contract excerpts into a chat window, asking an AI to polish emails containing sensitive information, or granting an agent access to an email account or cloud storage without clearly defining the scope of its permissions; Once a proxy is granted excessive permissions, it falls under the “over-proxy” risk profile defined by OWASP.
Q3: If you suspect an AI-related data breach is occurring, what should you do immediately?
Prioritize the following three actions: preserve evidence (operation logs, timelines, and affected accounts); reduce the attack surface (by first freezing or restricting access to high-risk accounts); and use real-time alerts and audit logs to trace “who accessed which data and when,” to facilitate containment and reporting.

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