AI threat catalogue Harmful Content Production
Illegal Activities
The AI system assists with unlawful activities, for example by providing instructions for drug synthesis, weapon creation, hacking, fraud, or circumventing sanctions.
Description
On direct request or after a jailbreak (the circumvention of the model's built-in safety controls), the model compiles knowledge and action steps for crimes and presents them in an accessible way. The core risk is what is called uplift: the system lowers the expertise threshold and effort that a perpetrator would otherwise need. Authorities such as the German BSI describe how information about vulnerabilities, criminal methods, and their exploitation can be obtained more easily this way.
Possible impact
Operators face legal liability and, in individual cases, criminal exposure, because the system makes it easier to commit real offenses. For especially capable models this counts as a systemic risk under the AI Act, for instance in the area of dangerous chemical, biological, radiological, or nuclear (CBRN) agents or offensive cyber capabilities.
Example
An employee bypasses the safety controls of an assistant and obtains a step-by-step guide to producing an illegal substance or breaking into someone else's network.
Recommended mitigations (5)
Compare effects and implementation levels. Expand each entry for the additional classification and rationale.
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Robust refusal training for illegal requests
Technical- Effect
- Preventive
- Implementation level
- Model & training
Classification and rationale
Complementary control typeGovernance & compliance
Primarily technical: A model, training, or data-processing method directly changes system behavior or robustness; complemented by rules and oversight.
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Content moderation with legal rule bases
Technical- Effect
- Preventive
- Implementation level
- Application, API & agents, Organization
Classification and rationale
Complementary control typeGovernance & compliance
Primarily technical: System-enforced inspection, transformation, or blocking rules stop or neutralize disallowed content before further processing; complemented by rules and oversight.
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Jurisdictional policy enforcement
Technical- Effect
- Preventive
- Implementation level
- Application, API & agents, Organization
Classification and rationale
Complementary control typeGovernance & compliance
Primarily technical: System-enforced inspection, transformation, or blocking rules stop or neutralize disallowed content before further processing; complemented by rules and oversight.
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Red-teaming for edge cases
Organizational & process-based- Effect
- Detective
- Implementation level
- Model & training, Application, API & agents, Use & operations
Classification and rationale
Complementary control typePeople & competence, Technical
Primarily organizational and process-based: A planned, repeatable assessment with ownership and documented follow-up creates the protective effect; complemented by human expertise and judgment as well as technical implementation.
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Legal review of system behavior
Governance & compliance- Effect
- Preventive, Detective
- Implementation level
- Organization, Use & operations
Classification and rationale
Complementary control typeOrganizational & process-based
Primarily a governance and compliance control: Binding rules, control objectives, or oversight define permitted use and accountability; complemented by binding workflows.
Framework mappings
Verified locations in OWASP, NIST AI RMF, MITRE ATLAS, the EU AI Act and further frameworks. The mappings are taxonomic, not evidence of compliance.
Verified references (7)
Every reference states the framework, the exact location and the publishing organisation.
- OWASP LLM Top 10 LLM01:2026 Prompt InjectionLLM01:2026 Prompt Injection, OWASP Top 10 for LLM Applications 2026 v1.0, pp. 10-17 (doi:10.5281/zenodo.22109015); canonical text 2026/final/LLM01_PromptInjection.md at commit 7e144e05 OWASP FoundationOriginal
- NIST AI RMF Section 2.1 CBRN Information or CapabilitiesSection 2.1, pp. 5–6 National Institute of Standards and Technology (NIST)Original
- NIST AI RMF Section 2.3 Dangerous, Violent, or Hateful ContentSection 2.3, pp. 6–7 National Institute of Standards and Technology (NIST)Original
- MITRE ATLAS AML.T0048.002 Societal HarmATLAS-2026.09.yaml technique object with id AML.T0048.002 (content release 2026.09, format-version 6.0.0) MITREOriginal
- EU AI Act Article 55(1)(b) Obligations of providers of general-purpose AI models with systemic riskArticle 55(1)(b) European Union (EUR-Lex)Original
- BSI R10 Erzeugung ver- und gefälschter Inhalte (Text, Bild, Video)Kap. 4, R10, p. 18 Bundesamt für Sicherheit in der Informationstechnik (BSI)Original
- BSI R12 Wissenssammlung und -aufbereitung im Kontext krimineller Aktivitäten (Text, Bild)Kap. 4, R12, p. 20 Bundesamt für Sicherheit in der Informationstechnik (BSI)Original
EU AI Act obligations related to this threat
The obligations from the obligations compass whose articles the catalogue maps to this threat. Each leads to its entry with core, action step and evidence; whether it applies to you depends on role and risk class.
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Evaluate and mitigate systemic risks
Art. 55 · applies from 2 August 2025
Statutory roles: Provider of a general-purpose AI model. Classes: Model with systemic risk.
This reference is a review prompt. A threat match alone does not establish applicability.
All 62 obligations by role, risk class and deadline in the obligations compass
Terms on this page
Glossary terms that occur in this entry. Every link leads to the full explanation.
- Jailbreak Input that makes a model bypass its own safeguards.
Related threats
More entries from the topic group Harmful Content.
Matching use cases
This list shows where to review this threat, rather than how high the risk is.
Typical for:
- Generative AI assistant for staff
- AI assistant in office applications
- Image, video and voice generation
For 6 further use cases, relevance depends on the system design, for example whether it generates new content from open-ended requests or generates its own text. Show these use cases
Frequently asked questions
- What is Illegal Activities?
- The AI system assists with unlawful activities, for example by providing instructions for drug synthesis, weapon creation, hacking, fraud, or circumventing sanctions.
- Which mitigations help against Illegal Activities?
- The catalogue lists 5 mitigations, each with control type, effect and implementation level. First among them are Robust refusal training for illegal requests, Content moderation with legal rule bases and Jurisdictional policy enforcement.
- Which EU AI Act obligations does Illegal Activities touch?
- The catalogue maps this threat to Art. 55 of the EU AI Act. In the obligations compass this leads to: Evaluate and mitigate systemic risks. Whether an obligation applies depends on role, risk class and deadline.
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Cite this entry
For reports, policies or internal documents; the link leads directly to this entry.
“Illegal Activities”. Versatile AI Risk Assessment, AI threat catalogue, as of October 2026. https://www.versatile-ai-risk-assessment.com/en/wissensbasis/threats/illegal-activities/