Results for “integrity-manifest”

Comprehensive LLM security testing prompts for bias detection, data leakage, alignment testing, and adversarial prompt resistance.

Detect and defend against prompt injection hidden in documents, web pages, and images consumed by an agent.

Read-only OWASP LLM Top 10 audit of app-facing AI features: prompt injection, data leak, supply chain, poisoning, unsafe output, excessive agency, system-prompt leak, RAG/embedding risks, misinformation, unbounded consumption. Use when "audit LLM security", "prompt injection", "jailbreak my chatbot", "is my AI safe".

Implement continuous identity verification for zero trust using phishing-resistant MFA (FIDO2/WebAuthn), risk-based conditional access, and identity governance aligned with the CISA Zero Trust Maturity Model.

Register AI agents on Ethereum mainnet using ERC-8004 (Trustless Agents). Use when the user wants to register their agent identity on-chain, create an agent profile, claim an agent NFT, set up agent reputation, or make their agent discoverable. Handles bridging ETH to mainnet, IPFS upload, and on-chain registration.

Guides the implementation of ethical AI principles, including fairness auditing, bias mitigation, explainability, accountability, and privacy protection in machine learning systems.

Audit a project for destructive-operation and migration safety gaps, then produce a phased safeguard plan. Use when "is my migration safe", "could I lose data", "my agent might delete prod", or "safe schema changes". Restore drills and RPO/RTO belong to plan-backup-dr. Source transforms → audit-codemod-safety.

AI Manipulation Defense System with self-learning prompt injection detection and adaptive mitigation

Enriches vague, low-detail prompts into structured, agent-optimized XML before execution. INVOKE IMMEDIATELY — before any tool use or file reads — when you detect any of these signals: prompt under 10 words with no file path or error message; vague action verbs with no object ("fix the bug", "make it better", "clean this up", "refactor this", "optimize performance", "improve the UI", "add authentication", "add payments", "add notifications", "build the feature"); CLARIFIER_ADVISORY in your context window; user says "clarify", "help me describe this", "enrich this prompt", "structure my request". Also triggers on: "make this work", "it's broken", "it looks bad", "add X" with no further detail, "implement Y" with no constraints. Do NOT trigger on: prompts ending with ?, prompts containing error messages or stack traces, prompts with specific file paths, prompts already containing acceptance criteria or success metrics.