LLM Data Exfiltration

Secure60 detects sensitive data egress through AI systems — copilots, chatbots, AI APIs and internal LLM deployments. Detection combines pattern-based rules with behavioural analysis (UEBA) to identify when AI tools are being used to extract or leak sensitive information.

What It Detects

Data Leakage via Copilots and Chatbots

Users (or compromised accounts) using AI assistants to extract sensitive data — customer records, credentials, financial data, proprietary code, or internal documents. Detection covers both intentional extraction and accidental exposure through overly broad AI access.

Sensitive Data in AI Responses

AI systems returning content that contains PII, credentials, API keys, or other sensitive data that should not appear in responses. Monitors for patterns that indicate the AI has access to data it should not be surfacing.

Anomalous AI Usage Patterns

Unusual patterns of interaction with AI systems — high-volume querying, systematic data extraction, off-hours usage from unusual locations, or interaction patterns that differ significantly from the user’s baseline. These detections use Secure60’s entity analytics (UEBA) to establish baselines and flag deviations.

How It Works

Data exfiltration detection requires visibility into AI interactions. This is achieved by ingesting logs from your AI systems into Secure60, where both rule-based and behavioural detections evaluate the traffic.

The detection approach combines:

• Pattern matching — Rules that identify known exfiltration techniques and sensitive data patterns in AI interactions.
• Behavioural analysis — UEBA models that establish per-user baselines for AI usage and flag anomalies.
• Cross-correlation — Combining AI interaction data with other security signals (e.g. a user who triggered a phishing detection also making unusual AI queries).

Configuration

Work with Secure60 to enable data exfiltration detection:

1. Ensure AI interaction logs are flowing into Secure60 (same integration path as prompt-attack detection).
2. Enable the managed detection rules for data exfiltration.
3. Configure sensitivity levels for sensitive data pattern matching.
4. Allow UEBA baseline models to establish normal usage patterns (typically 2-4 weeks).

Getting Started

Contact Secure60 to discuss your AI deployment landscape and what log sources are available. The team will help you set up the appropriate integrations and detection rules.