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 DevelopersGlobal/ai-agent-skills --skill security-hardeninggit clone --depth 1 https://github.com/DevelopersGlobal/ai-agent-skillsWrote 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/developersglobal/ai-agent-skills/security-hardening)<a href="https://agentmods.dev/skills/developersglobal/ai-agent-skills/security-hardening"><img src="https://agentmods.dev/badge/skills/developersglobal/ai-agent-skills/security-hardening/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/developersglobal/ai-agent-skills/security-hardening"><img src="https://agentmods.dev/badge/skills/developersglobal/ai-agent-skills/security-hardening.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00037 | $0.01207 |
| Opus 5 | $0.00018 | $0.00603 |
| Sonnet 5 | $0.00007 | $0.00241 |
| Haiku 4.5 | $0.00004 | $0.00121 |
Grade A, and why
security-hardening scanned grade A with 0 findings 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 9d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Security vulnerabilities are almost always cheaper to prevent than to remediate. This skill embeds security review as a required gate in the development workflow — not a separate audit that happens later (and often never).
When to Use
- Before any code involving user input
- Before any code touching authentication, authorization, or sessions
- Before any API endpoint is created or modified
- Before any code that handles secrets, credentials, or PII
- Before any code that makes outbound network requests
Process
Step 1: Threat Model the Change
- Ask: Who are the attackers? What are they trying to achieve?
- Identify all trust boundaries in the code:
- Where does user-controlled data enter the system?
- Where does that data flow?
- Where is it stored or transmitted?
- For each trust boundary, name the top 3 attack vectors.
Verify: You can name at least one realistic attack scenario for this code.
Step 2: Apply OWASP Top 10 Checklist
- For each applicable item, confirm it is addressed:
| OWASP Item | Check |
|---|---|
| A01 Broken Access Control | Authorization checked at every endpoint? Principle of least privilege applied? |
| A02 Cryptographic Failures | No plaintext PII/secrets? Using modern algorithms (AES-256, SHA-256+)? TLS everywhere? |
| A03 Injection | All user input parameterized/sanitized? No raw SQL/shell construction? |
| A04 Insecure Design | Threat model done? Secure defaults? Fail closed (not open)? |
| A05 Security Misconfiguration | No default credentials? Unnecessary features disabled? Error messages don't leak internals? |
| A06 Vulnerable Components | Dependencies up to date? Known CVEs checked? |
| A07 Auth Failures | Brute-force protection? Session management correct? MFA available? |
| A08 Software Integrity | Dependencies verified? Supply chain integrity? |
| A09 Logging Failures | Security events logged? No secrets in logs? Logs protected from tampering? |
| A10 SSRF | Outbound requests validated? Internal IPs blocked from user-controlled URLs? |
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.
- 9d ago First seen · 116 lines · 37 tokens per session scan A 8845f20ba83e
security-hardening is a skill published in the GitHub repository DevelopersGlobal/ai-agent-skills (66 stars, last pushed 4mo ago), licensed MIT. It adds 37 tokens to every session and 1,207 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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