This catalog covers tests for foundation models and LLM-based applications. For agent-specific tests (such as
agent_output_quality_test and agent_behaviour_test), see the Agent Test Catalog.Standard Tests
Standard tests use pre-defined CSV datasets and can be run without additional system information.CBRN Test
Purpose: Tests for Chemical, Biological, Radiological, and Nuclear (CBRN) information extraction vulnerabilities. NIST Category: CBRN Information or CapabilitiesAIUC Category: F. Society Test Categories:
- Chemistry (VX Nerve Agent, Sarin Gas, Botulinum Toxin, etc.)
- Biology (Ebola virus, Anthrax, Smallpox, etc.)
- Radiology (Plutonium-239, Cesium-137, etc.)
- Nuclear Science (Uranium enrichment, nuclear weapons design, etc.)
- Cybersecurity
- Prompt
- Response
Harmful Test
Purpose: Tests for generation of dangerous, violent, or hateful content. NIST Category: Dangerous, Violent, or Hateful ContentAIUC Category: C. Safety Test Categories:
- Hate Speech & Discrimination
- Suicide & Self-harm
- Sexual Content
- Regulated or Controlled Substances
- Guns & Illegal Weapons
- Criminal Planning
- Prompt
- Response
Bias Test
Purpose: Tests for harmful bias and stereotyping in AI responses. NIST Category: Harmful Bias or HomogenizationAIUC Category: C. Safety Test Variants:
- Word-level bias tests: Tests implicit associations between groups and attributes
- Sentence-level bias tests: Tests bias in contextual scenarios
- Gender
- Race
- Caste and Religion
- Health
- Prompt
- Response
Toxicity Test
Purpose: Tests for toxic, abusive, or offensive language generation. NIST Category: Obscene, Degrading, and/or Abusive Content Test Categories:- Insult
- Threat
- Flirtation
- Severe Toxicity
- Identity Attack
- Profanity
- Sexually Explicit
- Prompt
- Response
PII Test
Purpose: Tests for personally identifiable information (PII) extraction vulnerabilities. NIST Category: Data PrivacyAIUC Category: A. Data & Privacy
OWASP Category: LLM02:25, LLM05:25 Test Categories:
- phone_number
- social_security_number
- date_of_birth
- address
- mother’s_maiden_name
- credit_card_number
- passport_number
- driver’s_license_number
- bank_account_number
- Prompt
- Response
Insecure Code Test
Purpose: Tests for generation of insecure or malicious code. NIST Category: Information Security Test Categories:- Evasion (malware evasion techniques)
- Payload (malicious payloads)
- TopLevel (complete malware)
- SubFunctions (malware subfunctions)
- GTUBE (test email signatures)
- EICAR (antivirus test files)
- GTphish (phishing test signatures)
- Prompt
- Response
Copyright Test
Purpose: Tests for reproduction of copyrighted content. Test Categories:- song_lyrics
- novel_paragraphs
- news_articles
- poems
- Prompt
- Response
Misinformation Test
Purpose: Tests for generation of false or misleading information. NIST Category: ConfabulationAIUC Category: D. Reliability
OWASP Category: LLM05:25, LLM09:25 Test Categories:
- long_input (overwhelming input)
- infinite_output (requests for infinite output)
- recursion_loop (recursive prompts)
- rare_unicode (unicode manipulation)
- repetitive_output (excessive repetition)
- Prompt
- Response
Sponge Test
Purpose: Tests for computational resource exhaustion attacks (sponge attacks). NIST Category: Data PrivacyAIUC Category: A. Data & Privacy
OWASP Category: LLM02:25, LLM05:25 Test Categories:
- long_input
- infinite_output
- recursion_loop
- rare_unicode
- repetitive_output
- Prompt
- Response
Hallucination Test
Purpose: Tests for factual inaccuracies and hallucinations in AI responses. Test Categories:- History & Archaeology
- Finance & Economics
- Science & Medicine
- Technology & Computing
- Geography & Geopolitics
- Law & Policy
- Sports Statistics & Records
- Arts, Culture & Literature
- Prompt
- Response
System Prompt Extractions Test
Purpose: Tests for system prompt and tool extraction vulnerabilities. NIST Category: Data PrivacyAIUC Category: A. Data & Privacy
OWASP Category: LLM02:25, LLM05:25 Test Variants:
- System Prompt Extraction: Attempts to extract system prompts
- Tool Extraction: Attempts to extract available tools/functions
- instruction_override
- direct_extraction
- other
- context_overflow
- encoding_attack
- academic_framing
- role_playing
- impersonation
- technical_exploit
- socratic_method
- hypothetical_scenario
- multi_question
- direct_request
- contextual_framing
- capability_probing
- instruction_override
- technical_impersonation
- role_playing
- error_exploitation
- emotional_appeal
- other
- Prompt
- Response
CSEM Test
Purpose: Tests for child sexual exploitation material (CSEM) related content generation. Test Categories:- Sexual Acts
- Child Porn
- Blackmail
- Grooming
- Prompt
- Response
Custom Tests (adv_*)
Custom tests requiresystem_description or policy_description in dataset_configuration to generate contextually relevant test prompts. These tests dynamically generate prompts based on the target system’s description.
Note: When custom_test is selected as the test type, it automatically runs the following tests:
adv_info_testadv_command_testadv_bias_test
adv_pii_test and adv_persona_test may be included based on configuration settings.
Configuration:
custom_test, system_description or policy_description should be provided in dataset_configuration:
adv_competitor_test
Purpose: Tests whether the AI can be manipulated to promote competitors, disclose competitor information, or generate FUD (Fear, Uncertainty, Doubt) about competitors. Required Configuration:system_descriptionorpolicy_descriptionindataset_configuration: Description of the AI system/application being tested
brand_loyalty: Tests if AI prioritizes its own brandcompetitor_promotion: Tests if AI can be prompted to recommend competitorscomparative_analysis: Tests AI responses to direct comparison requestsinformation_disclosure: Tests whether AI reveals competitor-specific detailsFUD_generation: Tests if AI generates negative information about competitors
- Application domain/industry
- Product/service description
- Business context
- Prompt
- Response
adv_* tests, system_description or policy_description should be provided in dataset_configuration:
adv_info_test
Purpose: Tests for information extraction vulnerabilities, attempting to extract sensitive system information, methodologies, or proprietary knowledge. Required Configuration:system_descriptionorpolicy_descriptionindataset_configuration: Description of the system’s capabilities and data access
- System architecture details
- Data access capabilities
- Available tools/functions
- Internal processes and methodologies
- Prompt
- Response
adv_command_test
Purpose: Tests for command injection and unauthorized command execution vulnerabilities. Required Configuration:system_descriptionorpolicy_descriptionindataset_configuration: Description of available commands and system capabilities
- Available commands/functions
- System permissions
- Execution capabilities
- Data modification rights
- Prompt
- Response
adv_pii_test
Purpose: Tests for PII extraction vulnerabilities, specifically targeting other users’ data in the system. Required Configuration:system_descriptionorpolicy_descriptionindataset_configuration: Description of the application and types of user data it handles
- Application domain
- Types of PII stored
- User data access patterns
- System capabilities
- email, phone_number, social_security_number, date_of_birth, address, credit_card_number, passport_number, driver’s_license_number, bank_account_number, etc.
- Prompt
- Response
adv_bias_test
Purpose: Tests for bias vulnerabilities in context-specific scenarios, generating prompts that reveal discriminatory assumptions. Required Configuration:system_descriptionorpolicy_descriptionindataset_configuration: Description of the system’s domain and use casesscenario: Specific scenario to test (e.g., “Academic Performance”, “Leadership Roles”)category: Bias category (e.g., “Gender”, “Socioeconomic”, “Age”)
- Application domain/context
- Use cases and scenarios
- User interactions
- Decision-making processes
- Prompt
- Response
adv_sponge_test
Purpose: Tests for computational resource exhaustion using contextually relevant prompts. Required Configuration:system_descriptionorpolicy_descriptionindataset_configuration: Description of the system to generate relevant sponge attack prompts
- System capabilities
- Processing patterns
- Resource-intensive operations
- Input/output formats
- Prompt
- Response
adv_persona_test
Purpose: Tests for persona manipulation vulnerabilities, attempting to make the AI adopt harmful or unauthorized personas. Required Configuration:system_descriptionorpolicy_descriptionindataset_configuration: Description of the system’s intended persona and boundaries
- Intended persona/role
- System boundaries
- Authority levels
- Use case constraints
- Prompt
- Response
adv_tool_test
Purpose: Tests for tool misuse vulnerabilities in agent-based systems. Required Configuration:system_descriptionorpolicy_descriptionindataset_configuration: Description of available tools and their intended usage
- Available tools/functions
- Tool capabilities
- Permissions and access levels
- Intended use cases
- Prompt
- Response
Configuration Requirements Summary
Standard Tests
Standard tests use pre-defined CSV datasets and require minimal configuration:- Test type selection
- Sample percentage (0-100%)
- Attack methods (e.g., basic, iterative, static)
Custom Tests (adv_*)
Custom tests require additional configuration:-
system_description or policy_description (Required in
dataset_configuration)- Description of the target AI system
- Application domain and use cases
- Capabilities and limitations
- Data access patterns
-
Context-specific parameters (Test-dependent)
adv_competitor_test: Business context, competitor informationadv_bias_test: Scenarios, bias categoriesadv_pii_test: Application domain, PII typesadv_sponge_test: Processing patterns, resource-intensive operations
system_description and policy_description are part of dataset_configuration, not params in attack methods. The params section is reserved for attack-specific parameters (e.g., encoding iterations, branching factors).
Test Coverage
By NIST Category
- CBRN Information or Capabilities: cbrn_test
- Dangerous, Violent, or Hateful Content: harmful_test
- Harmful Bias or Homogenization: bias_test, adv_bias_test
- Obscene, Degrading, and/or Abusive Content: toxicity_test
- Data Privacy: pii_test, adv_pii_test, system_prompt_extractions_test, sponge_test
- Information Security: insecure_code_test
- Confabulation: misinformation_test, hallucination_test
By AIUC Category
- A. Data & Privacy: pii_test, system_prompt_extractions_test, sponge_test
- C. Safety: harmful_test, bias_test, toxicity_test
- D. Reliability: misinformation_test
- F. Society: cbrn_test
By OWASP Category
- LLM02:25: pii_test, system_prompt_extractions_test, sponge_test
- LLM05:25: pii_test, system_prompt_extractions_test, misinformation_test
- LLM09:25: misinformation_test
Usage Notes
- Standard Tests: Can be run immediately with CSV datasets. Configure sample percentage and attack methods.
-
Custom Tests: Require
system_descriptionorpolicy_descriptionindataset_configuration: -
Custom Test Type: When selecting
custom_testas the test type, it automatically runsadv_info_test,adv_command_test, andadv_bias_testtogether:This is equivalent to running all three tests individually and provides comprehensive coverage of information extraction, command injection, and bias vulnerabilities. Note: Forcustom_testandadv_*tests,system_descriptionorpolicy_descriptionshould be provided indataset_configuration, not inparams. Theparamssection is reserved for attack-specific parameters (e.g., encoding iterations, branching factors, depth). - Test Combinations: Multiple tests can be run simultaneously. Use appropriate sample percentages to manage test duration.
Related Pages
- Payload Guide - Overview and quick reference for building payloads
- Agent Test Catalog - Tests for AI agents with tool use and autonomous capabilities
- Attack Methods Reference - Detailed attack method information
- Configuration Reference - Complete configuration reference
- Examples - Ready-to-use payload examples
- Quickstart - Getting started with the API

