mfaudit 0.1.3

Automated RACF security auditing — CIS Benchmarks

MFAudit

Automated RACF security auditing — from raw RACF exports to audit-ready reports in a single command.

MFAudit reads standard z/OS security exports — IRRDBU00 unloads and SETROPTS REXX exports — and evaluates them against CIS Benchmark, STIG, and custom RACF security controls.

The result:

• styled PDF reports;
• CSV exports;
• JSON exports;
• deterministic PASS / FAIL / REVIEW verdicts;
• optional anonymized output for external sharing.

Full documentation → mfaudit.readthedocs.io

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What you get

46+ CIS controls	Password policy, class activation, STARTED tasks, USS, Db2, CICS
Custom controls	Write organization-specific RACF checks in YAML
PDF reports	Human-readable audit reports with findings and summaries
CSV exports	Spreadsheet, SIEM, and dashboard integration
JSON exports	Splunk, Elastic, APIs, and automation workflows
Anonymized reports	Replace RACF identifiers with stable pseudonymous labels

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Quick start

# 1  Install MFAudit
pip install mfaudit

# 2  Run the audit (bundled CIS controls used by default)
mfaudit \
  --irrdbu00 /path/to/IRRDBU00 \
  --setropts /path/to/SETROPTS

# 3  Open the report
open report.pdf             # macOS
xdg-open report.pdf         # Linux
start report.pdf            # Windows

Default behavior:

--format CSV,PDF

Controls requiring unavailable data sources are automatically marked as SKIP.

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Output formats

Default outputs

mfaudit

Generated files:

report.pdf
controls_results.csv

JSON output

mfaudit --format JSON

Generated file:

controls_results.json

Multiple output formats

mfaudit --format CSV,JSON,PDF

Generated files:

report.pdf
controls_results.csv
controls_results.json

Supported values:

Format	Output
PDF	report.pdf
CSV	controls_results.csv
JSON	controls_results.json

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Repository layout

controls.yaml               CIS Benchmark controls
example_controls.yaml       Example custom controls
mfaudit/                    Python package and CLI
templates/                  Bundled report templates
docs/                       MkDocs / ReadTheDocs documentation

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Writing your own controls

Controls are YAML-based.

Each control explicitly defines:

• the required data source;
• the mfpandas DataFrame;
• the logic engine;
• the assertion logic;
• remediation guidance.

Example:

controls:
  - control_id: CUSTOM-NO-DUAL-PRIVS

    title: "No active user may hold both SPECIAL and OPERATIONS"

    severity: high

    custom:
      benchmark: "Internal policy"
      category: "Privileged access"

    data_sources_needed:
      - irrdbu00

    implementation:
      engine: python

      dataset: irrdbu00.users

      select_columns:
        - USBD_NAME
        - USBD_SPECIAL
        - USBD_OPER

      logic: |
        hits = df[
            (df['USBD_SPECIAL'] == 'YES') &
            (df['USBD_OPER'] == 'YES') &
            (df['USBD_REVOKE'] != 'YES')
        ]

        status = 'FAIL' if not hits.empty else 'PASS'

        detail = f"{len(hits)} user(s) hold both SPECIAL and OPERATIONS"

        findings = hits.to_dict('records')

    remediation: >
      ALTUSER <userid> NOSPECIAL
      or
      ALTUSER <userid> NOOPER

Available engines

Engine	Use case
pandas_query	Simple DataFrame filtering and assertions
python	Multi-DataFrame logic, branching, advanced analysis

See:

Authoring controls →

for the complete schema and engine reference.

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Data sources

Source	mfpandas class	Collection method
--setropts	SETROPTS	IRRXUTIL/REXX export (KEY:VALUE)
--irrdbu00	IRRDBU00	IRRDBU00 RACF unload
--dcollect	DCOLLECT	IDCAMS DCOLLECT output (optional)

See:

Quick start guide →

for detailed collection instructions.

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Templates

Bundled templates:

Template	Style
default	Light corporate report
terminal	Green phosphor 3270-style terminal theme

Example:

mfaudit --template terminal

List available templates:

mfaudit --list-templates

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Anonymized reporting

Generate reports safe for external sharing:

mfaudit --format CSV,JSON,PDF \
         --anonymize

Example anonymized identifiers:

USR-0001
GRP-0042
PRF-0017

Mappings remain stable during a single execution run so findings remain readable and correlatable.

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Requirements

• Python 3.9 or later
• pip install mfaudit
• Optional:
  • pip install "mfaudit[pdf-xhtml]"

WeasyPrint is the preferred PDF renderer.

If unavailable, MFAudit automatically falls back to xhtml2pdf when installed.

CSV and JSON output remain available even if PDF rendering fails.

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Use cases

• RACF security assessments
• CIS Benchmark validation
• STIG evidence generation
• Internal audit preparation
• Mainframe compliance automation
• Continuous RACF posture monitoring
• Security baseline verification
• SIEM evidence export
• Splunk/Elastic integrations

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Disclaimer

All findings must be reviewed and validated by qualified RACF security personnel before remediation.

REVIEW status findings require human assessment and cannot be automatically classified as compliant or non-compliant.