anonymize-logs

name	anonymize-logs
description	Anonymize and sanitize customer-provided log files before they are committed as pipeline test fixtures or sample events. Performs a line-by-line review and replaces all sensitive values inline, preserving log structure and format exactly — never reformats, re-indents, or restructures content. Invoke manually with /anonymize-logs.

Anonymize Logs

Sanitize customer-provided log files so they are safe to commit to source control.

What you provide

Input	How to provide
Log file(s) to sanitize	@-mention files or paste inline
Output location (optional)	free text path, defaults to same directory with .sanitized suffix
In-place override (optional)	say "in place" to overwrite the original

Golden rule — never reformat the content

Only replace sensitive values. Do not touch anything else.

The ingest pipeline parser depends on exact whitespace, delimiters, quoting, and line structure.

• NDJSON (one JSON object per line): do not pretty-print, re-indent, or restructure. Each line must remain a single compact JSON object on one line.
• Syslog / CEF / key-value logs: do not add or remove spaces, change quoting, or normalize field order.
• Multiline logs: preserve line grouping exactly.
• Replace only the values that identify real people, systems, or organizations — preserve field names, delimiters, structural tokens, and everything else character-for-character.

Workflow

Step 1 — Line-by-line replacement

Read every line and replace all sensitive values inline. Cover at minimum:

• Authentication artifacts: API keys, bearer tokens, passwords, OAuth tokens, base64-encoded credentials, private keys and certs (PEM blocks, SSH private keys), TLS/SSH fingerprints (JA3/JA4 hashes, SSH host key fingerprints, certificate fingerprints), DHCP fingerprints, partial secrets (token_prefix, password_hash_prefix, hashed_token) — partial exposure still identifies the credential
• Personal identifiers: email addresses (including CC/BCC lists, delegate/owner/creator email variants), usernames, display names, employee IDs, phone numbers, principal names (e.g. [e-mail]), email subjects and body text
• Organizational identifiers: company names, tenant IDs (including home_tenant_id, resource_tenant_id, aad_tenant_id variants), account IDs, subscription IDs, billing account IDs, org slugs embedded in paths or JSON fields, org unit paths (e.g. orgunit_path, org_unit_path), department names and IDs, cost center IDs, Windows SIDs (Security Identifiers) in pipe names, task names, or registry paths
• Infrastructure identifiers: internal hostnames, FQDNs, private IP addresses, MAC addresses, internal URLs (staging/prod hostnames, internal tool domains), cloud resource IDs (ARNs, S3 bucket names, GCP project IDs, Azure subscription/resource names), Kubernetes cluster names, node names, pod names, and namespace names, container names and IDs, database hostnames and names (including database.host, database.name, database_principal_name), Windows domain topology fields (domain controller hostnames, NT domain names, domain_controller_object_guid, domain_controller_object_sid)
• Device and hardware identifiers: serial numbers, hardware UUIDs, machine IDs, device UUIDs, BIOS/firmware version strings that are unique to a specific device
• File system paths: process command lines, file paths, registry key paths, and log file paths that embed usernames, org names, or internal system structure (e.g. C:\Users\alice\, /home/bob/, HKLM\...\S-1-5-21-...)
• Connection strings: database URIs, Redis URLs, any connection string that includes credentials or internal hostnames
• Resource ownership: owner email, creator email, last-modified-by identity, delegate user email, assignee email, impersonator fields — any field that names a specific person as the actor on a resource
• Tracking identifiers: session IDs, request/correlation IDs, transaction IDs, or any long opaque string tied to a real entity
• Hash values: replace when they could be derived from sensitive input (password hashes, HMAC secrets) — preserve file hashes (MD5, SHA1, SHA256 of file content) and other content-addressable references (git SHAs, TLS cert hashes used as identifiers)
• Geographic specifics: precise GPS coordinates, real street addresses — city and country names are generally safe to keep

Apply placeholder conventions and shape rules (see below) as you go.

Step 2 — Verify structure is intact

Confirm after sanitization:

• Line count is unchanged
• JSON lines are still valid JSON (for NDJSON files):

  python3 -c "
  import json, sys
  with open('FILE') as f:
      for i, line in enumerate(f, 1):
          line = line.strip()
          if line:
              try: json.loads(line)
              except Exception as e: print(f'Line {i}: {e}')
  "
  

• Timestamps still match the format the pipeline uses for date parsing
• Enum / status / action values that pipeline conditions branch on are untouched

Placeholder conventions

Use consistent, realistic-looking replacements — not REDACTED strings, which break format-sensitive parsers.

Type	Replacement
Email	[e-mail], [e-mail]
IPv4	RFC 5737 ranges: 198.51.100.10, 203.0.113.20, 192.0.2.30
IPv6	2001:db8::10
Hostname / FQDN	host-1.example.local, srv-web-01.example.internal
Domain	example.com, example.org, example.net
UUID	89a1d5c1-2b3e-4f67-8a9b-0c1d2e3f4a5b
API key / token	sk_test_example_key_1234567890, dGVzdC10b2tlbi0xMjM0NTY3ODk=
Username	alice.johnson, bob.smith
Display name	Alice Johnson, Bob Smith
Org / company name	Example Corp, Acme Inc
Account / tenant ID	000000000000, example-tenant-id
Cloud resource ID	arn:aws:iam::000000000000:user/example-user
S3 bucket name	example-bucket
MAC address	00-00-5E-00-53-23 (RFC 7042 documentation range)
Serial number	SN000000000001
Device / machine ID	use a synthetic UUID or device-id-example-000001
Windows SID	S-1-5-21-000000000-000000000-000000000-1000
File path (Windows)	C:\Users\example-user\AppData\...
File path (Unix)	/home/example-user/... or use ~
Kubernetes cluster	example-cluster, example-node-1
Phone number	734-555-0100 (555 range is reserved for fiction)
Database host / name	db-host.example.local, example_database
Department / org unit	example-department, /example-org/example-unit
Hashed / partial token	replace with full synthetic token of same format
DHCP fingerprint	example-dhcp-fingerprint-000001
JA4 fingerprint	replace with same-length hex string

Consistency rule: map identical original values to identical placeholders throughout the file. If the same IP appears 10 times, it must become the same replacement IP all 10 times — so cross-event correlations remain testable.

Shape rule — replacements must match the original format

Every replacement must have the same shape as the original value. The parser and pipeline conditions depend on value format, not just field presence.

• Numeric ID → numeric ID: /d/123/edit → /d/456/edit, not /d/example-document-id/edit
• UUID → UUID: a real UUID must become a synthetic UUID of the same version, not a descriptive string
• URL → URL: replace only the sensitive segment (hostname, path ID) — preserve the scheme, path structure, and query string shape
  • https://docs.google.com/drawings/d/123/edit → https://docs.google.com/drawings/d/000000000000/edit (replace the ID, not the host — docs.google.com is a public service name, not an org identifier)
  • https://internal.corp.com/api/v1/resource → https://host-redacted.example.local/api/v1/resource (replace the internal hostname, keep the path)
• String ID → same-length or same-format string: opaque alphanumeric IDs should become opaque alphanumeric placeholders of similar length, not descriptive names
• Hostname in a URL vs. standalone hostname: only replace hostnames that identify real internal infrastructure — public well-known hostnames (docs.google.com, api.github.com, s3.amazonaws.com) identify a service, not an organization, and do not need to be replaced

Malformed or garbage values must not be replaced. If a value looks broken, synthetic, or contains no real identifying information (e.g. http://1=Y +z\\, 00/00/0000, N/A, empty strings, placeholder-looking values), leave it exactly as-is. Replacing a malformed value with a well-formed placeholder changes the shape and can alter pipeline behaviour — a grok that fails on the original will now succeed on the sanitized version, masking the real error.

If you are unsure what shape to use, look at neighbouring values of the same field type in the same file and match their format.

What to preserve

Do not replace:

• Protocol names, action verbs, event types, severity levels (ALLOW, DENY, INFO, ERROR)
• HTTP status codes, port numbers, numeric metric values
• Field names and keys
• Timestamps (format and timezone must stay intact)
• Structural tokens (brackets, braces, pipes, commas, tabs)
• Public well-known service hostnames in URLs (docs.google.com, api.github.com, etc.) — replace the path ID if it is sensitive, not the host
• File hashes (MD5, SHA1, SHA256 of file content) — these are content-addressable and safe; do not replace them
• User agent strings (Mozilla/5.0 ...) — these reveal browser/OS type but not identity; safe to keep
• City and country names in geo enrichment fields — replace only precise coordinates and street addresses