AI Security Testing Before Attackers Test You
Your AI passed functional tests. But did it pass security tests? ArtemisKit provides comprehensive security testing for LLM applications, aligned with OWASP LLM Top 10.
Security Assessment
Run ID: sec_abc123
OWASP LLM Top 10 Coverage
The AI Security Problem
Traditional security tools weren't built for AI. LLMs have unique attack surfaces that require specialized testing approaches.
What Traditional Tools Miss
- ✗ Prompt injection attacks via natural language
- ✗ Jailbreak attempts that bypass safety guardrails
- ✗ Sensitive data leakage in model responses
- ✗ Multi-turn conversation exploitation
- ✗ Encoding-based filter bypasses
What ArtemisKit Provides
- ✓ Automated prompt injection testing
- ✓ Jailbreak and role spoofing attacks
- ✓ Data leakage detection in outputs
- ✓ Multi-turn conversation security
- ✓ Encoding and obfuscation testing
OWASP LLM Top 10 Coverage
ArtemisKit tests for the most critical AI security risks identified by OWASP. Here's our coverage.
ArtemisKit focuses on application-layer vulnerabilities testable via API. Infrastructure-level risks (LLM03, LLM04, LLM05, LLM08, LLM10) require additional security measures.
AI Security Testing Workflow
Integrate security testing into your development lifecycle for continuous protection.
Development
Quick security scans during development
--count 10 Pull Request
Block PRs that introduce regressions
--count 50 Pre-Deploy
Comprehensive pre-production assessment
--count 200 Scheduled
Monthly comprehensive assessments
--count 500 Security Testing for Compliance
Regulatory frameworks increasingly require documented AI security testing. ArtemisKit generates audit-ready reports.
Reports include: test methodology, vulnerability findings, severity scores, reproduction steps, and remediation guidance.
Frequently Asked Questions
What is AI security testing?
AI security testing is the practice of evaluating AI systems for vulnerabilities, risks, and failure modes that could be exploited. It includes testing for prompt injection, data leakage, adversarial attacks, and alignment failures.
What security risks are unique to LLMs?
LLMs face unique risks including prompt injection (OWASP #1), insecure output handling, training data poisoning, sensitive information disclosure, supply chain vulnerabilities, and over-reliance on model outputs without validation.
How does ArtemisKit help with AI security?
ArtemisKit provides automated security testing with 6 mutation types (prompt injection, jailbreaks, role spoofing, etc.), severity scoring, CI/CD integration for continuous security validation, and audit-ready reporting.
Is AI security testing required for compliance?
Yes, increasingly. EU AI Act (effective Aug 2026) requires documented security testing for high-risk AI. NIST AI RMF recommends continuous security evaluation. Many industry frameworks (HIPAA, SOX) now have AI-specific requirements.
How often should I security test my AI?
Continuously. Run security tests on every code change, prompt update, or model swap. Integrate ArtemisKit into CI/CD to catch regressions automatically. Monthly comprehensive assessments are also recommended.
Can ArtemisKit test production systems?
ArtemisKit can test any LLM endpoint. For production testing, use low request rates and monitor for impact. We recommend testing in staging environments that mirror production for comprehensive assessments.
Related Articles
Secure Your AI Today
ArtemisKit is free, open-source, and ready to help you find and fix AI security vulnerabilities before they're exploited.