Personal Information Tagging for Logs
draft-irtf-pearg-pitfol-00
Network Working Group S. Rao
Internet-Draft S. Nagaraj
Intended status: Experimental Grab
Expires: March 14, 2021 S. Sahib
R. Guest
Salesforce
September 10, 2020
Personal Information Tagging for Logs
draft-irtf-pearg-pitfol-00
Abstract
Software systems typically generate log messages in the course of
their operation. These log messages (or 'logs') record events as
they happen, thus providing a trail that can be used to understand
the state of the system and help with troubleshooting issues. Given
that logs try to capture state that is useful for monitoring and
debugging, they can contain information that can be used to identify
users. Personal data identification and anonymization in logs is
crucial to ensure that no personal data is being inadvertently logged
and retained which would make the logging system run afoul of laws
around storing private information. This document focuses on
exploring mechanisms that can be used by a generating or intermediary
logging service to specify personal or sensitive data in log
message(s), thus allowing a downstream logging server to potentially
enforce any redaction or transformation.
Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
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Drafts is at https://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
Rao, et al. Expires March 14, 2021 [Page 1]
Internet-Draft PITFoL September 2020
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on March 14, 2021.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Motivation and Use Cases . . . . . . . . . . . . . . . . . . 4
4. Challenges with Existing Approaches . . . . . . . . . . . . . 4
5. Proposed Model . . . . . . . . . . . . . . . . . . . . . . . 5
5.1. Defining the log privacy schema . . . . . . . . . . . . . 5
5.2. Typical Workflow . . . . . . . . . . . . . . . . . . . . 7
5.3. Log Processing and Access Control . . . . . . . . . . . . 7
6. Examples . . . . . . . . . . . . . . . . . . . . . . . . . . 8
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 9
8. Security Considerations . . . . . . . . . . . . . . . . . . . 9
9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 10
10. Normative References . . . . . . . . . . . . . . . . . . . . 10
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 10
1. Introduction
Logs capture the state of a software system in operation, thus
providing observability. However, because of the amount of state
they capture, they can often contain sensitive user information
[link: twitter storing passwords]. Personal data identification and
redaction is crucial to make sure that a logging application is not
storing and potentially leaking users' private information. There
are known precedents that help discover and extract sensitive data,
for example, we can define a regular expression or lookup rules that
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