G7 Hiroshima Code action 1: lifecycle risk management and pre-deployment testing

Identify, evaluate and mitigate risks across the lifecycle, incl. testing before deployment

By Jorge García Aibar Reviewed 2026-09-24

From clause to evidence Build the artefact, then file every output it produces as a record that names AIGE-OBL-G7-A1. Drawn from chapter 08.

Text alternative

Clause: G7 Code, Action 1.
Duty holder: Organisations developing advanced AI….
Applies from: No date, Voluntary.
Artefact: Adversarial red-team suite.
Layer: Layer 03 Evals & Red Teaming as Evidence.
Evidence record: Evidence record v1.
Record schema: Evidence record.
The same topic in 19 other frameworks; the crosswalk section below links each clause.

Id: AIGE-OBL-G7-A1
Instrument: G7 Hiroshima Process International Code of Conduct for Advanced AI Systems code
Clause: Action 1
In scope: Organisations developing advanced AI systems
Applies from: No date Voluntary · agreed 2023-10-30

The artefact that evidences it

Adversarial red-team suite; eval gate.

L3 Evals & Red Teaming as Evidence

What this obligation connects to Solid edges are direct relations, dashed ones looser (a case that cites the same article, a framework whose clauses only touch the topic); patterns and controls take the colour of their stack layer. Select a node to open it; the lists below give every relation in full.

Data table: every relation

Relations of AIGE-OBL-G7-A1
Family	Item	Relation
Same crosswalk topic	AI Verify 4.1.1, 6.1.1, 5.2.1, 5.9.1, 4.8.1	Core clause
Same crosswalk topic	CSA AICM MDS-06, MDS-07, AIS-05, MDS-12, MDS-03	Core clause
Same crosswalk topic	China Deep Synthesis DeepSyn Art. 15, DeepSyn Art. 20	Core clause
Same crosswalk topic	CoE Convention CoE Art. 16(2)(g)	Core clause
Same crosswalk topic	EU AI Act Art. 15, Art. 55, Art. 60, Art. 15(3), Art. 9, Art. 42(3), Art. 53, Art. 51, Art. 56	Core clause
Same crosswalk topic	GAO AI Accountability 3.7, 3.2	Core clause
Same crosswalk topic	GB/T 45654 GB/T 45654 Security assessment	Core clause
Same crosswalk topic	GPAI Code Safety 3.2, Safety C6, Transparency 1.1, Safety C1, Safety C7	Core clause
Same crosswalk topic	ISO 42001 A.6, 9.1	Core clause
Same crosswalk topic	Korea AI Act Art. 32(1), Art. 32	Core clause
Same crosswalk topic	NIST AI RMF MEASURE 2, MEASURE 2.7, MEASURE 2.1, MEASURE 1	Core clause
Same crosswalk topic	OECD AI Principles OECD 1.4	Core clause
Same crosswalk topic	Singapore Agentic Agentic 2.3.2	Core clause
Same crosswalk topic	Singapore GenAI GenAI 5, GenAI 6, GenAI 8	Core clause
Same crosswalk topic	TC260 Framework 3.0 TC260 3, TC260 App. 2 II.6, TC260 5.3.14	Core clause
Same crosswalk topic	China GenAI Measures GenAI Art. 17, GenAI Art. 7	Related clause
Same crosswalk topic	GDPR Art. 32	Related clause
Same crosswalk topic	OWASP Agentic ASI05	Related clause
Same crosswalk topic	OWASP LLM LLM01:2026	Related clause

Patterns that build it

No pattern in the catalogue names this clause on its "Maps to" line yet; the artefact above is the engineering answer.

The same topic in other frameworks

From the topic crosswalk: the clauses filed under the same topics as this one. Mappings are illustrative, not a claim of conformity.

Robustness, security and evaluations

EU AI Act Art. 15 Accuracy, robustness and cybersecurity (core)
EU AI Act Art. 55 Obligations for providers of general-purpose AI models with systemic risk (core)
ISO 42001 A.6 AI system life cycle (core)
NIST AI RMF MEASURE 2 MEASURE 2: AI systems are evaluated for trustworthy characteristics (core)
TC260 Framework 3.0 TC260 3 Technological countermeasures (core)
TC260 Framework 3.0 TC260 App. 2 II.6 Sandbox validation and red teaming (core)
China Deep Synthesis DeepSyn Art. 15 Technology management and algorithm verification (core)
China Deep Synthesis DeepSyn Art. 20 Security assessment of new products (core)
GB/T 45654 GB/T 45654 Security assessment Security-assessment requirements for generative AI services (core) (clause not verified)
GPAI Code Safety 3.2 Measure 3.2: Model evaluations (core)
NIST AI RMF MEASURE 2.7 MEASURE 2.7: AI system security and resilience as identified in the MAP function are evaluated and documented (core)
CSA AICM MDS-06 Adversarial Attack Analysis (core)
CSA AICM MDS-07 Robustness against Adversarial Attack / Model Hardening (core)
Singapore GenAI GenAI 5 Testing and Assurance (core)
Singapore GenAI GenAI 6 Security (core)
Singapore Agentic Agentic 2.3.2 Before deploying, test agents (core)
CoE Convention CoE Art. 16(2)(g) Testing before first use and when significantly modified (core)
OECD AI Principles OECD 1.4 Robustness, security and safety (core)
GAO AI Accountability 3.7 Assessment: assess performance against defined metrics to ensure the AI system functions as intended and is sufficiently robust (core)
AI Verify 4.1.1 Safety (technical test): run use-case benchmarks and red-teaming to evaluate for safety and possible harms (e.g. hallucination, toxicity) (core)
AI Verify 6.1.1 Robustness (technical test): compare accuracy with and without added noise to document and monitor performance (core)
AI Verify 5.2.1 Security: conduct security risk assessments that model threats and risks to the AI system (core)
EU AI Act Art. 60 Testing of high-risk AI systems in real-world conditions outside AI regulatory sandboxes
ISO 42001 9.1 Monitoring, measurement, analysis and evaluation
TC260 Framework 3.0 TC260 5.3.14 Resilience
China GenAI Measures GenAI Art. 17 Security assessment
EU AI Act Art. 15(3) Declared accuracy levels and metrics
EU AI Act Art. 9 Risk management system
EU AI Act Art. 42(3) Presumption of conformity for cybersecurity (Cyber Resilience Act)
GPAI Code Safety C6 Commitment 6: Security mitigations
GDPR Art. 32 Security of processing
NIST AI RMF MEASURE 2.1 MEASURE 2.1: Test sets, metrics, and details about the tools used during TEVV are documented
NIST AI RMF MEASURE 1 MEASURE 1: Appropriate methods and metrics are identified and applied
CSA AICM AIS-05 Application Security Testing
OWASP LLM LLM01:2026 Prompt Injection
OWASP Agentic ASI05 Unexpected Code Execution (RCE)
Korea AI Act Art. 32(1) Safety duties for AI above the compute threshold
GAO AI Accountability 3.2 Metrics: define performance metrics that are precise, consistent, and reproducible
AI Verify 5.9.1 Security: release AI systems only after appropriate and effective security checks and evaluation

GPAI and foundation models

EU AI Act Art. 53 Obligations for providers of general-purpose AI models (core)
EU AI Act Art. 55 Obligations of providers of general-purpose AI models with systemic risk (core)
GPAI Code Transparency 1.1 Drawing up and keeping up-to-date model documentation (core)
GPAI Code Safety C1 Commitment 1: Safety and Security Framework (core)
Korea AI Act Art. 32 Safety duties for AI above the compute threshold (core)
EU AI Act Art. 51 Classification of general-purpose AI models as general-purpose AI models with systemic risk
EU AI Act Art. 56 Codes of practice
GPAI Code Safety 3.2 Measure 3.2: Model evaluations
GPAI Code Safety C7 Commitment 7: Safety and Security Model Reports
CSA AICM MDS-12 Open Model Risk Assessment
CSA AICM MDS-03 Model Documentation
Singapore GenAI GenAI 8 Safety and Alignment R&D
China GenAI Measures GenAI Art. 7 Lawful data and foundation-model sources
AI Verify 4.1.1 Safety (technical test): run benchmarks and red-teaming to evaluate a generative model for safety and possible harms
AI Verify 4.8.1 Safety: identify and prevent content that violates laws or is harmful, including CBRN information and offensive cyber capabilities

Source

Chapter 08, section Treaty and international soft law, checked against its sources on the review date above.

Machine-readable

This obligation: /api/v1/obligations/aige-obl-g7-a1.json
The register: /api/v1/obligations.json · CSV
Schema and stability promise: open data and API

Cite this obligation

García Aibar, J. (2026). G7 Hiroshima Code action 1: lifecycle risk management and pre-deployment testing (AIGE-OBL-G7-A1). In AI Governance Engineering: The Thesis & Body of Knowledge (v0.5.0). https://doi.org/10.5281/zenodo.22956197. https://aigovernanceengineer.com/obligations/aige-obl-g7-a1. CC BY 4.0

BibTeX

@misc{aige2026obligation,
  author       = {Jorge García Aibar},
  title        = {{G7 Hiroshima Code action 1: lifecycle risk management and pre-deployment testing (AIGE-OBL-G7-A1)}},
  howpublished = {In AI Governance Engineering: The Thesis \& Body of Knowledge},
  year         = {2026},
  version      = {0.5.0},
  doi          = {10.5281/zenodo.22956197},
  url          = {https://aigovernanceengineer.com/obligations/aige-obl-g7-a1},
  note         = {Version 0.5.0}
}