In enterprise data loss prevention scenarios, a risk alert is often only the starting point of an investigation.For example, a system may detect that a user has sent an Excel file externally via email. From the alert, the organization can quickly identify basic information such as the file name, user, endpoint device, event time, and the application used for external transmission. However, for a complete data leakage investigation, simply knowing “who sent which file and when” is far from enough.
Security administrators also need to determine:
- Whether the file contains sensitive information;
- What operations were performed on the file before it was sent externally;
- Whether the file was transferred from another user;
- Whether the file was downloaded, saved as a new file, edited, or further distributed after transmission;
- Whether there are other files or historical activities with similar content;
- Whether there are related behaviors, similar risk events, or broader data flow chains.
If these questions must be answered manually by searching, filtering, and correlating email logs, endpoint logs, file operation logs, and application behavior records, the investigation process becomes highly time-consuming and prone to missing critical evidence.
Ping64 Data Loss Prevention provides Data Leakage Tracing, a comprehensive analysis view designed for the full lifecycle of a data leakage incident. When the system detects external file transmission, abnormal file movement, or suspected leakage behavior, administrators can access the Ping64 Data Leakage Tracing details page to analyze the current event from multiple dimensions, quickly restore the data flow process, identify related risks, and support subsequent auditing and response.
Flow Tracing: Restore File Transfer Paths Across Users and Endpoints
In real business environments, sensitive files rarely remain on a single user account or endpoint. A file may go through multiple stages such as email transfer, download, opening, editing, copying, saving as a new file, moving to another directory, or being sent externally again, forming a complex data flow path.
For example, User A may operate on a sensitive file from a local endpoint and send it to User B via email. After downloading the file, User B may open it, edit it, save it as a new file, or even send it externally again. Without effective flow tracing, administrators would typically need to query logs from both User A’s and User B’s endpoints, then manually compare file names, paths, timestamps, applications, and operation records.
Once the file is renamed, saved as a new copy, or moved to another directory, the relationship between the previous and subsequent actions can easily be broken, making it difficult to reconstruct the full incident chain.
With Ping64 Data Leakage Tracing, flow tracing correlates the sender, recipient, and subsequent file activities, helping administrators expand from a single log entry to a complete event chain.
Administrators can trace forward from User A’s operation node to see who received the file, or trace backward from User B’s file node to identify where the file came from. In other words, when a sensitive file or abnormal operation is discovered on User B’s endpoint, the administrator can trace it back to User A’s sending activity. Likewise, when an external transmission is detected from User A, the administrator can continue tracking how the file was handled after being received by User B.
Through flow tracing, data leakage investigations are no longer limited to a single user, endpoint, or log entry. Instead, organizations can build a complete file-centric flow chain across users, endpoints, and applications, enabling more accurate assessment of the source, path, and impact scope of a data leakage incident.
Similarity Correlation: Expand From a Single Alert to Related Risk Investigation
Flow tracing helps restore the transmission path of the current file. However, in a data leakage investigation, organizations also need to determine whether the current alert is an isolated incident or one node within the continuous movement of a certain type of sensitive data.
If the investigation relies only on file names, file paths, or a single operation type, many related risks may remain hidden. This is especially true when sensitive content has been copied, reorganized, rewritten, split, or saved again under a different name or location. In such cases, traditional search methods often struggle to identify the underlying connections.
Ping64 Data Leakage Tracing provides similarity correlation capabilities based on semantic vector search and sensitive rule overlap analysis. It automatically identifies historical behavior records that are similar in content and risk characteristics to the current leakage event, helping administrators expand from a single alert to a more complete risk view.
Semantic Vector Search: Identify Historical Records With Similar Content
In real-world data flow scenarios, sensitive content may appear repeatedly in different forms. For example, the same set of customer quotation information may be copied into a new Excel file, reorganized into a document, included in an email body, or entered into an AI conversation.
Ping64 uses semantic vector search to identify similar information at the content level. Even when file names and storage paths are different, the system can still discover historical activities related to the current leakage event based on semantic features.
For example, if the current alert involves the external transmission of a file containing customer quotation information, the system can further search historical records for similar quotation content, related customer information, or operations involving the same type of business data. This helps administrators uncover potentially related incidents.
Sensitive Rule Overlap Analysis: Determine Whether Risk Characteristics Match
Content similarity alone is not sufficient for a complete risk assessment. Whether different events match the same or similar sensitive rules is also an important basis for evaluating their relevance.
For example, the current event may trigger sensitive rules related to customer information, quotation data, and contract numbers. If historical behavior records also match the same types of sensitive rules, these events may have a higher level of correlation.
Ping64 combines sensitive rule overlap analysis to compare the risk characteristics of different events, helping administrators determine whether they involve the same category of sensitive data. This reduces omissions and false judgments caused by relying solely on keyword searches.
Multi-Channel Correlation: Discover Different Forms of Sensitive Data Flow
The value of similarity correlation lies not only in finding similar files, but also in identifying where sensitive data appears across different channels.
Ping64 can correlate multiple types of activities, including email transmission, printing, AI conversations, and file operations, based on content semantics and sensitive rules. This helps organizations discover how sensitive data flows through different business scenarios and application channels.
Through multi-channel correlation, administrators can start from a single external transmission alert and further identify related files, similar content, matching sensitive rules, and potential downstream distribution. This enables a more comprehensive assessment of the incident’s impact scope.
From Risk Detection to Audit Review: Building a Complete Response Loop
Ping64 Data Leakage Tracing is more than a log query capability. It is designed for the complete investigation process of data leakage incidents, helping organizations systematically answer key questions: where the file came from, who handled it, where it went, whether it continued to spread, and whether similar risks exist.
With flow tracing and similarity correlation, organizations can quickly restore the file source, transfer path, subsequent destination, and potential related risks from a single alert, significantly improving investigation efficiency and risk assessment accuracy.
Ping64 Data Leakage Tracing can also work with capabilities such as leakage channel analysis, sensitive information identification, related behavior chains, and screen recording to further enhance the response loop from risk detection and incident investigation to impact assessment and audit review. This helps enterprises build a more proactive, precise, and traceable data security protection system.
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