ai-security
This skill should be used when the user asks to "scan AI systems for security threats", "check for prompt injection vulnerabilities", "assess model security posture", "detect data poisoning risks", or "audit AI/ML pipeline security".
npx skills add majiayu000/claude-skill-registry --skill ai-security --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# AI Security > **Category:** Engineering > **Domain:** AI/ML Security ## Overview The **AI Security** skill provides specialized threat scanning for AI and machine learning systems. It identifies vulnerabilities unique to AI workloads including prompt injection, data poisoning, model extraction, adversarial inputs, and insecure model serving configurations. ## Clarify First Before running the scan, confirm these inputs. If any is unknown or vague, ASK — do not assume: - [ ] **Scan target & path** — which codebase or directory to analyze (sets `--path` and what gets scanned) - [ ] **Threat categories** — all, or specific (prompt-injection, data-poisoning, model-extraction, adversarial-input, insecure-serving) (sets `--category`) - [ ] **Severity threshold & context** — full audit vs pre-deployment gate (sets `--min-severity` and whether zero high/critical findings is a hard gate) Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact. ## Quick Start ```bash # Scan a codebase for AI-specific security threats python scripts/ai_threat_scanner.py --path ./my-ai-project # Scan with JSON outp
- Overview
- Clarify First
- Quick Start
- Tools Overview
- aithreatscanner.py
- Workflows
- Full AI Security Audit
- Pre-Deployment Security Gate
- Reference Documentation
- Common Patterns
- Prompt Injection Prevention
- Secure Model Loading
- Rate-Limited Inference API
Scan a codebase for AI-specific security threats python scripts/ai_threat_scanner.py --path ./my-ai-project Scan with JSON output python scripts/ai_threat_scanner.py --path ./my-ai-project --format json Scan only for prompt injection vulnerabilities python scripts/ai_threat_scanner.py --path ./src --category prompt-injection Scan with severity threshold python scripts/ai_threat_scanner.py --path ./src --min-severity high
What does the ai-security skill do?
This skill should be used when the user asks to "scan AI systems for security threats", "check for prompt injection vulnerabilities", "assess model security posture", "detect data poisoning risks", or "audit AI/ML pipeline security".
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill ai-security --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.