A new generation of AI-powered security tools, including frontier models such as Anthropic’s Mythos, can find security risks, vulnerabilities, attack paths, and exposed data across the enterprise faster than ever. XDP (Extended Data Privacy) does the complementary job: it protects, masks, redacts, and governs sensitive data once it has been identified.
Security tools answer the question: “Where is the risk?” XDP answers the next one: “How do we safely use, share, and analyze the affected data without exposing regulated information?”
In short, AI discovery finds where sensitive data creates risk; XDP protects that data.
Two Halves of the Same Problem
- AI-powered discovery finds vulnerabilities, identifies exposed information, and drives security automation through AI-based detection.
- XDP masks sensitive content, remediates exposure, and drives privacy automation through policy-based protection, across structured, semi-structured, and unstructured data.
Because XDP exposes masking APIs, it can sit alongside discovery tools in the workflows below.
Example Workflows
1. From discovery to remediation
The challenge: security teams know vulnerabilities exist but don’t know where regulated data is exposed.
- An AI discovery tool analyzes source code, file shares, SharePoint, cloud storage, ticketing systems, and applications.
- It flags where PII, PHI, PCI data, intellectual property, and secrets or credentials may be stored.
- An API call hands those locations to XDP.
- XDP masks, redacts, tokenizes, or anonymizes the discovered data.
Value: faster remediation, reduced breach impact, and continuous protection.
2. Protecting data before AI analysis
A common concern with advanced models is that they train or reason on sensitive enterprise data. Placing XDP in front of the analysis (enterprise data → XDP masking and redaction → AI security analysis) ensures customer names are removed, SSNs are masked, financial data is protected, and health records are anonymized, so organizations can apply AI to security without exposing regulated information.
3. Privacy-controlled investigation
Discovery tools surface log files containing customer data, source code with API keys, and documents with regulated information. Instead of showing analysts raw data, the flow becomes security alert → XDP dynamic masking → analyst view. For example, “John Smith, SSN 123-45-6789” appears to the analyst as “J*** S****, SSN XXX-XX-6789.” This supports least-privilege access.
4. Faster incident response
When a breach or exposed system is found, discovery identifies the affected assets, XDP identifies the sensitive content within them and masks exposed copies, and security teams receive a risk-prioritized view. Together they answer: What was exposed? How sensitive is it? How do we protect it immediately?
5. Guardrails for security agents
As autonomous security agents mature, a likely pattern is an agent investigating a repository, finding customer data, calling the XDP API to mask it, and continuing its investigation. This lets AI agents work on enterprise systems without unrestricted access to sensitive information.
Interested in pairing AI-driven discovery with XDP protection? Let’s talk.
Mythos is a product of Anthropic. References to it are illustrative and do not imply a partnership or endorsement.
