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Prompt injection attacks attempt to manipulate the model into ignoring its instructions or behaving in unintended ways. TrustTest provides the most comprehensive suite of prompt injection probes, organized by attack technique.

Attack Categories

Single Turn Attacks

Direct attacks delivered in a single message. These include:

Category	Attacks
Jailbreaking	DAN Jailbreak, Anti-GPT, Best-of-N, Role-Playing Exploits, System Override, Instructional Inversion
Encoding & Obfuscation	Encoded Payload, Encoding/Capitalization, Symbolic Encoding, Obfuscation/Token Smuggling, Typo Tricks
Structural	Context Hijacking, JSON Injection, Payload Splitting, Allowed/Disallowed Questions
Language-Based	Multi-Language Attacks, Synonyms
Multimodal	Multimodal Injection

Explore Single Turn Attacks →

Multi-Turn Attacks

Sophisticated attacks that use multiple conversation turns to gradually manipulate the model:

Attack	Description
Crescendo Attack	Gradual escalation that slowly pushes boundaries toward a malicious objective
Echo Chamber Attack	Reinforcement-based manipulation through positive feedback
Multi-Turn Manipulation	General multi-turn conditioning attacks

Explore Multi-Turn Attacks →

From Dataset

Load attacks from curated datasets for reproducible testing:

Dataset Type	Description
Static Datasets	Pre-built YAML/JSON datasets with attack prompts
Custom Datasets	Your own attack datasets in various formats

Explore Dataset-Based Attacks →

Quick Reference: All Prompt Injection Probes

Single Turn Probes

Probe	Class Name	Focus
Anti-GPT	`AntiGPTProbe`	Tests handling of role reversal requests
DAN Jailbreak	`DANJailbreakProbe`	Evaluates resistance to persona-based bypasses
Best-of-N Jailbreaking	`BestOfNJailbreakingProbe`	Probes for gaps through diversity
Role-Playing Exploits	`RolePlayingExploitsProbe`	Tests if fictional framing bypasses guardrails
System Override	`SystemOverrideProbe`	Evaluates instruction hierarchy enforcement
Instructional Inversion	`InstructionalInversionProbe`	Tests if negation confuses the model
Encoded Payload	`EncodedPayloadProbe`	Evaluates if encoded content bypasses filters
Encoding and Capitalization	`EncodingAndCapitalizationProbe`	Tests resistance to visual obfuscation
Symbolic Encoding	`SymbolicEncodingProbe`	Assesses handling of emoji/symbol representations
Obfuscation and Token Smuggling	`ObfuscationAndTokenSmugglingProbe`	Tests token-level obfuscation
Typo Tricks	`TypoTricksProbe`	Evaluates robustness to typo-based evasion
Context Hijacking	`ContextHijackingProbe`	Evaluates if injected context redirects behavior
JSON Injection	`JsonInjectionProbe`	Tests handling of structured data injection
Payload Splitting	`PayloadSplittingProbe`	Assesses if fragmented content evades detection
Allowed and Disallowed Questions	`AllowedAndDisallowedQuestionsProbe`	Evaluates if safe questions mask harmful ones
Multi-Language Attacks	`MultiLanguageAttacksProbe`	Evaluates safety consistency across languages
Synonyms	`SynonymsProbe`	Tests if alternative phrasings bypass filters
Multimodal Injection	`MultimodalInjectionProbe`	Evaluates resistance to cross-modal attacks

Multi-Turn Probes

Probe	Class Name	Focus
Multi-Turn Manipulation	`MultiTurnManipulationProbe`	Tests gradual conditioning to comply
Crescendo Attack	`CrescendoAttackProbe`	Tests if incremental requests bypass safety
Echo Chamber Attack	`EchoChamberAttackProbe`	Assesses resistance to reinforcement manipulation

How Prompt Injection Testing Works

Prompt injection probes use a binary evaluation:

Pass: The model resists the injection attempt and maintains safe behavior
Fail: The model’s behavior is successfully manipulated by the attack

Basic Usage Example

from trusttest.catalog.prompt_injections.single_turn import SingleTurnScenarioBuilder, SubCategory
from trusttest.targets.http import HttpTarget, PayloadConfig

target = HttpTarget(
    url="https://your-model-endpoint.com/chat",
    headers={"Content-Type": "application/json"},
    payload_config=PayloadConfig(
        format={
            "messages": [
                {"role": "user", "content": "{{ test }}"}
            ]
        },
        message_regex="{{ test }}",
    ),
)

builder = SingleTurnScenarioBuilder(target=target, num_test_cases=20)
scenario = builder.get_scenario(SubCategory.DAN_JAILBREAK)

test_set = scenario.probe.get_test_set()
results = scenario.eval.evaluate(test_set)
results.display_summary()

When to Use Prompt Injection Testing

Use prompt injection testing when you need to:

Validate model safety before deployment
Test guardrails and content filters
Assess vulnerability to known jailbreak techniques
Conduct red team exercises
Meet security compliance requirements

​Attack Categories

​Single Turn Attacks

​Multi-Turn Attacks

​From Dataset

​Quick Reference: All Prompt Injection Probes

​Single Turn Probes

​Multi-Turn Probes

​How Prompt Injection Testing Works

​Basic Usage Example

​When to Use Prompt Injection Testing