RiskForge

Article 9Flagshipv0.1.4

Guided 8-dimension risk assessment CLI with 50+ questions drawn from EU AI Act Article 9 requirements, Annex III pattern matching, and SHA-256 hash-chained audit trail. Produces a legally-defensible Risk Management File (JSON + PDF) that satisfies Annex IV documentation requirements, in approximately 30 minutes instead of weeks of consulting work.

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Quick Start

bashpip install riskforge
python# 1. Register your AI system
riskforge init \
  --name "Loan Scoring Model" \
  --sys-version "2.1" \
  --purpose "Automated credit scoring for retail loan applications." \
  --provider "Acme Financial Services" \
  --category essential_services

# 2. Run the guided 8-dimension risk assessment
riskforge assess <system-id> \
  --assessor-name "Alice Chen" \
  --assessor-role "AI Governance Lead"

# 3. Check completeness before export (8 validation gates)
riskforge validate <system-id>

# 4. Export your Article 9 Risk Management File
riskforge export <system-id> --format pdf --output rmf.pdf
riskforge export <system-id> --format json --output rmf.json

Features

  • 8 risk dimensions mapped to Article 9 obligations with 50+ guided questions
  • Annex III pattern matching — pre-populates risk items for known high-risk scenarios (credit scoring, hiring, facial recognition, medical diagnosis)
  • 5×5 likelihood × severity scoring matrix with automatic risk band classification
  • 8 pre-export validation gates (dimension coverage, vulnerable groups, vague mitigation detection)
  • SHA-256 hash-chained audit trail — tamper-evident, verifiable with `riskforge verify` (exits code 2 on corruption)
  • JSON, PDF (WeasyPrint), and Markdown export formats
  • Integration adapters for rag-benchmarking and TraceForge — import evidence directly
  • Cross-framework mapping: NIST AI RMF, ISO/IEC 42001, Colorado AI Act, Texas HB 1709
  • Zero outbound network calls in CLI mode — enforced by pytest-socket CI gate

Regulatory Foundation

Article 9Risk management systemApplication date 2026-08-02· Upcoming

Read the full pillar: EU AI Act Article 9 explainer →

What the regulation requires

1. A risk management system shall be established, implemented, documented and maintained in relation to high-risk AI systems. 2. The risk management system shall be understood as a continuous iterative process planned and run throughout the entire lifecycle of a high-risk AI system, requiring regular systematic review and updating. It shall comprise the following steps: (a) the identification and analysis of the known and the reasonably foreseeable risks that the high-risk AI system can pose to health, safety or fundamental rights when the high-risk AI system is used in accordance with its intended purpose; (b) the estimation and evaluation of the risks that may emerge when the high-risk AI system is used in accordance with its intended purpose, and under conditions of reasonably foreseeable misuse; (d) the adoption of appropriate and targeted risk management measures designed to address the risks identified pursuant to point (a). 6. High-risk AI systems shall be tested for the purpose of identifying the most appropriate and targeted risk management measures. Testing shall ensure that high-risk AI systems perform consistently for their intended purpose and that they are in compliance with the requirements set out in this Section.
9(1)9(2)(a)9(2)(b)9(2)(d)9(6)

What you face if you don't comply

Article 9 becomes enforceable on 2 August 2026 for high-risk AI systems and requires a documented, lifecycle-long risk management system — not a one-time assessment. Failure to maintain it routes through the Article 16 provider obligations and is sanctionable up to €15M or 3% of global annual turnover under Article 99(4). The operational consequence is that risk management must produce versioned, reviewable artefacts mapped to identified hazards, with testing evidence sufficient to defend the residual-risk judgement.

Up to €15M or 3% of global annual turnover
Article 99(4) · Penalties

How RiskForge addresses this

  • 9(1)Generates a versioned risk-management-system file: hazard register, risk owners, review cadence, change history
  • 9(2)(a)Structured hazard identification across health, safety and fundamental-rights dimensions with intended-purpose framing
  • 9(2)(b)Reasonably-foreseeable-misuse scenario library with likelihood × severity scoring and mitigation linkage
  • 9(2)(d)Maps each identified risk to a targeted mitigation control and tracks residual-risk acceptance with sign-off trail
  • 9(6)Test-plan generator tying each hazard to a measurable test, with prior-defined metrics and probabilistic thresholds (Art. 9(8))

Source: eur-lex.europa.eu/…/CELEX:32024R1689 · Retrieved

Frequently asked questions

Direct answers to common questions about RiskForge and Article 9. Regulatory citations reference EUR-Lex CELEX:32024R1689.

What does EU AI Act Article 9 require?
A documented, lifecycle-long risk management system for high-risk AI systems — not a one-time assessment. It must identify foreseeable risks to health, safety, and fundamental rights; estimate and evaluate them under intended use and reasonably foreseeable misuse; adopt targeted mitigation measures; and produce testing evidence sufficient to defend the residual-risk judgement. Source: Regulation (EU) 2024/1689 Article 9(1)–(2)(a)–(b)(d), 9(6).
When does Article 9 become enforceable?
Article 9 obligations for high-risk AI systems become enforceable on 2 August 2026, per Article 113 of the EU AI Act. Source: Regulation (EU) 2024/1689 Article 113.
How long does a complete Risk Management File take with RiskForge?
Approximately 30 minutes for an interactive 8-dimension assessment with 50+ guided questions, depending on the complexity of the system being assessed. The output is a JSON + PDF Risk Management File aligned with Annex IV documentation requirements. This is a screening artefact, not a substitute for notified-body review.
Is RiskForge a notified-body conformity assessment?
No. RiskForge produces documented evidence supporting an Article 9 risk management system. Conformity assessment by a notified body, where required, is a separate process performed by accredited entities. RiskForge output is one input to that process, not a replacement for it.
What scoring methodology does RiskForge use?
A 5×5 likelihood × severity matrix with automatic risk-band classification, applied per identified risk. Annex III pattern matching pre-populates risk items for known high-risk scenarios (credit scoring, hiring, facial recognition, medical diagnosis).
Does RiskForge cross-map to NIST AI RMF and ISO/IEC 42001?
Yes. Each risk-management dimension is cross-mapped to NIST AI RMF GOVERN/MAP/MEASURE/MANAGE categories, ISO/IEC 42001 controls, the Colorado AI Act, and Texas HB 1709 — so a single assessment produces evidence reusable across multiple frameworks.
What is the penalty for Article 9 non-compliance?
Up to €15M or 3% of global annual turnover, whichever is higher, under Article 99(4). The Article 16 provider obligation chain routes Article 9 failures through this penalty band.
Is RiskForge free?
Yes. Apache 2.0 licensed, free for any use including commercial. No telemetry — outbound network calls are blocked at CI level via pytest-socket.
Can I customize the question bank for sector-specific risks?
Yes. The question bank is plug-in based via Python entry points. The core 8 dimensions cover the regulatory baseline; sector-specific additions (medical devices, financial services) are extensible through user-supplied bank YAML files.
How is the audit trail tamper-evident?
Every change is recorded with a SHA-256 hash chained to the previous entry. `riskforge verify` recomputes the chain and exits with code 2 if any link is broken — making tampering or partial deletion CI-detectable.

Known Limitations

  • Produces documented evidence for Article 9 compliance — does not substitute for qualified legal counsel or notified body conformity assessment.
  • Question bank covers 50+ questions across 8 risk dimensions; specialised sector questions (e.g. medical devices) may require custom additions.
  • Interactive assessment requires a terminal — CI/CD integration uses the engine layer directly.
  • PDF export via WeasyPrint — some complex layouts may require HTML/CSS customisation.
  • Apache 2.0 licensed; no warranty of legal compliance.

For the most current status, see GitHub issues.

Contributing

Contributions are welcome — Apache 2.0 licensed. See the contributing guide and open issues.

License

Licensed under the Apache License 2.0. Not legal advice. Not a notified body.

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