AI Security
Prompt Injection Vulnerability Tester
Evaluate your LLM application's resilience against direct and indirect prompt injection attacks.
This tool assesses your AI application's defenses across five critical control areas: input validation, system prompt protection, output filtering, privilege separation, and user context isolation. Based on OWASP Top 10 for LLM Applications guidance, it generates a vulnerability score that helps security teams prioritize hardening efforts before production deployment.
Assessment Results
Configure defense controls to assess prompt injection vulnerability.
Vulnerability Summary
Defense Breakdown
| Control Area | Status |
|---|---|
| Input Validation | - |
| System Prompt | - |
| Output Filtering | - |
| Privilege Separation | - |
| Context Isolation | - |
Risk Composition
Hardening Priorities
- Input Validation: Implement strict allowlist filtering and parameterized prompt templates to block injection payloads.
- System Prompt: Encrypt or isolate system prompts so they cannot be extracted or overridden by user input.
- Output Filtering: Deploy content guardrails and output validators to prevent data exfiltration through responses.
- Privilege Control: Apply least-privilege principles to any tools or APIs accessible by the LLM agent.
- Context Isolation: Ensure per-user session boundaries to prevent cross-tenant prompt injection attacks.
Security Disclaimer
This tool provides a high-level vulnerability estimate based on self-reported controls. It does not replace penetration testing or formal red-teaming exercises. Results should be validated by security professionals before production decisions.
AI Security Disclaimer
This assessment aligns with OWASP Top 10 for LLM Applications but is simplified for rapid evaluation.
- Prompt injection is the #1 vulnerability in LLM applications per OWASP.
- Use this score alongside automated testing and manual red-teaming.
- Coordinate remediation with your AI security and engineering teams.
Search topics covered
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How to use this calculator
Evaluate Input Defenses
Start by selecting the level of input validation applied to user prompts before they reach the LLM. Strict regex and allowlist filtering blocks known injection patterns. Basic sanitization offers partial protection but can be bypassed. No validation leaves the application fully exposed to direct injection attacks.
Assess Prompt Protection
Evaluate whether system prompts are protected from extraction. If users can trick the model into revealing its instructions, attackers can craft targeted bypasses. Encrypted or isolated system prompts significantly reduce this risk vector.
Review Output Controls
Check whether response outputs are filtered for sensitive data, harmful content, or unintended instruction execution. Content guardrails and moderation layers prevent the LLM from leaking data or executing injected commands through its responses.
Check Privilege Boundaries
Assess what tools, APIs, or data sources the LLM can access. Autonomous tool access with no approval gates creates the highest risk since injected prompts could trigger real-world actions like database queries, email sends, or code execution.
Verify Context Isolation
Confirm whether user sessions are isolated. Shared context across users means one user's injected prompt could influence another user's session, enabling cross-tenant attacks. Full session isolation eliminates this vector entirely.
Review And Export
The vulnerability score combines all five control areas into a weighted index. Export the assessment as PDF or CSV to share with your security team. Reassess after every application update, model change, or new tool integration.
Advantages of this calculator
OWASP Aligned Framework
The assessment maps directly to OWASP Top 10 for LLM Applications, ensuring your evaluation language matches industry standards used by auditors and security researchers worldwide.
Multi-Layer Defense Model
Unlike simple checklists, this tool evaluates five distinct defense layers simultaneously, reflecting how real-world prompt injection attacks exploit gaps across multiple control areas at once.
Rapid Pre-Deployment Check
Security teams can assess LLM application readiness in minutes rather than waiting for full penetration test results, enabling faster go/no-go decisions for production deployments.
Clear Remediation Guidance
The breakdown table shows exactly which controls are weak, helping engineering teams focus hardening efforts on the highest-impact areas rather than applying generic security measures.
Repeatable Assessment Cycle
The structured format enables consistent reassessment after model updates, prompt changes, or new tool integrations, creating a trend line of application security posture over time.
Executive Communication
The risk tier and classification translate complex AI security concepts into business language that executives and compliance officers can understand and act on quickly.
Governing bodies & standards
Q&A
What is prompt injection?
Prompt injection is an attack where malicious input overrides the LLM's system instructions, causing it to perform unintended actions, leak data, or bypass safety controls.
What is indirect prompt injection?
Indirect injection occurs when malicious instructions are embedded in external data sources (websites, documents, emails) that the LLM processes, rather than direct user input.
Can prompt injection be fully prevented?
No single control eliminates the risk entirely. Defense-in-depth with input validation, output filtering, privilege control, and monitoring provides the strongest protection.
How often should I test for prompt injection?
Test after every model update, prompt change, new tool integration, or major application release. Continuous automated testing is recommended for production applications.
Does this replace penetration testing?
No. This is a rapid self-assessment tool. Formal red-teaming and penetration testing by security professionals should complement this evaluation.