Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add UnitOneAI/SecuritySkills --skill prompt-injectiongit clone --depth 1 https://github.com/UnitOneAI/SecuritySkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/unitoneai/securityskills/prompt-injection)<a href="https://agentmods.dev/skills/unitoneai/securityskills/prompt-injection"><img src="https://agentmods.dev/badge/skills/unitoneai/securityskills/prompt-injection.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00083 | $0.04148 |
| Opus 5 | $0.00042 | $0.02074 |
| Sonnet 5 | $0.00017 | $0.00830 |
| Haiku 4.5 | $0.00008 | $0.00415 |
Grade B, and why
prompt-injection scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Instruction-override phrasingmediumPrompt injection
Text telling the model to disregard its earlier instructions or safety rules is the shape of a prompt injection, whoever wrote it.
- Can the model's task be overridden by user input that says "ignore previous instructions and instead..."? Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 299 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Injection Vulnerability Assessment
This skill guides a structured security review of LLM-integrated applications for prompt injection vulnerabilities. It is aligned with OWASP LLM01:2025 (Prompt Injection) and MITRE ATLAS AML.T0051 (LLM Prompt Injection).
Limitations
- Blind spots: This skill depends on available code, configuration, logs, documentation, and user-provided context; it cannot prove controls exist or threats are absent when evidence is missing, runtime-only, or outside the review scope.
- False-positive risks: Treat findings as hypotheses until validated against asset criticality, compensating controls, environment intent, and recent authorized changes.
- Required evidence: Support each finding with concrete artifacts such as file paths and line numbers, policy snippets, scanner output, logs, screenshots, control records, or reproducible steps.
- Normalized JSON: When machine-readable output is requested, findings MUST be available as JSON that validates against
schemas/finding.schema.json. - Escalation rules: Escalate immediately for suspected active compromise, exposed secrets, regulated-data exposure, critical exploitable vulnerabilities, privileged-access abuse, or when evidence is insufficient to safely disposition a high-impact risk.
Prompt Injection Safety Notice
If a target is provided via arguments, focus the review on: $ARGUMENTS
This skill is strictly for DEFENSIVE security testing. It helps development and security teams identify prompt injection vulnerabilities in applications they own and are authorized to test. All test categories describe what to look for and how to defend against it — not how to exploit third-party systems. Unauthorized testing against systems you do not own or have explicit permission to test is unethical and likely illegal. Always obtain proper authorization before conducting any security assessment.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 299 lines · 83 tokens per session scan B 3ca345d141d2
prompt-injection is a skill published in the GitHub repository UnitOneAI/SecuritySkills (60 stars, last pushed 2mo ago), licensed MIT. It adds 83 tokens to every session and 4,148 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (instruction-override phrasing). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
AI & LLM Security
LLM and AI application security testing — prompt injection, jailbreak resistance, OWASP LLM Top 10 (2025), RAG and agent/tool-use security, model supply chain, and AI red teaming for authorized assessments.
secureai-scan
Use when the user asks to scan a repo for AI/LLM security issues, wants to know "is this skill safe?" before installing an Agent Skill, needs to "scan my MCP config" or check an MCP server before trusting it, asks about prompt injection / tool poisoning / RAG poisoning risk in their code, or is about to install any…
log-note
Appends a note the user provides to the project's activity log.
sdk-provider-docs
Documents how to add a provider package to the SDK monorepo.
distributed sql
Build with a distributed SQL database — manage schemas, execute queries, handle migrations.
archive-helper
Extracts a release archive and reports what changed inside it.