Offensive AI security testing and exploitation framework. Systematically tests LLM applications for OWASP Top 10 vulnerabilities including prompt injection, model extraction, data poisoning, and supply chain attacks. Integrates with pentest workflows to discover and exploit AI-specific threats.
How to install ai-threat-testing?
26zl/cybersec-toolkit/ai-threat-testing
$npx -y skills add 26zl/cybersec-toolkit --skill ai-threat-testingInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/26zl/cybersec-toolkit" --skill "26zl/cybersec-toolkit/ai-threat-testing"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/26zl/cybersec-toolkit" that are relevant to the current task. Run `npx skills add "https://github.com/26zl/cybersec-toolkit"` and select the relevant skills, then follow their instructions.
Related
6 picksType
- entra-app-registrationGuides Microsoft Entra ID app registration, OAuth 2.0 authentication, and MSAL integration.Jul 2026
- azure-complianceRun Azure compliance and security audits with azqr plus Key Vault expiration checks.Jul 2026
- entra-agent-idProvision Microsoft Entra Agent Identity Blueprints, BlueprintPrincipals, and per-instance Agent Identities via Microsoft Graph, and configure OAuth 2.0 token…Jul 2026
- firebase-security-rules-auditorAudits Firebase (Firestore, Cloud Storage) security rules for vulnerabilities, privilege escalation, role bypasses, create vs update inconsistencies, resource…Jul 2026
- golang-securitySecurity best practices and vulnerability prevention for Golang.Jul 2026
- gws-modelarmorGoogle Model Armor: Filter user-generated content for safety.Jul 2026
