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 codebygarv/Ai-skills --skill jwt-security-hardenergit clone --depth 1 https://github.com/codebygarv/Ai-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/codebygarv/ai-skills/jwt-security-hardener)<a href="https://agentmods.dev/skills/codebygarv/ai-skills/jwt-security-hardener"><img src="https://agentmods.dev/badge/skills/codebygarv/ai-skills/jwt-security-hardener.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 | $0.00025 | $0.00405 |
| Opus 5 | $0.00013 | $0.00202 |
| Sonnet 5 | $0.00005 | $0.00081 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
jwt-security-hardener 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 4d 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.
What it actually says
Purpose
Audit and harden JSON Web Token (JWT) authentication, signing, and verification pipelines to eliminate critical vulnerabilities: algorithm confusion (alg: none, HMAC vs RSA/ECDSA confusion), weak signing secrets, missing claim validations, and lack of revocation mechanisms.
When to Use
- Implementing or reviewing JWT authentication for APIs, single sign-on, or microservices.
- Passing security audits and penetration tests on token validation logic.
- Setting up token rotation, refresh token revocation, and asymmetric key pairs (JWKS).
What to Analyze
- Algorithm Whitelisting: Explicitly enforcing expected algorithms (e.g.
algorithms: ['RS256']) preventingnoneor public-key-as-HMAC attacks. - Mandatory Standard Claims: Enforcing
exp(short expiration, max 15m),iat,nbf,iss(issuer validation), andaud(audience validation). - Storage Security: Storing tokens in
HttpOnly,Secure,SameSite=Laxcookies vs vulnerablelocalStorage. - Token Revocation & Blacklisting: Redis blocklist for revoked
jti(token IDs) upon logout or permission change. - Asymmetric Key Rotation: Fetching public verification keys via standard JWKS endpoints with key caching.
Output Format
- Security Vulnerability Assessment: Critical / High risks found in current JWT setup.
- Hardened Verification Code: Drop-in secure token validation middleware.
- JWKS Key Rotation Specification: Standard asymmetric key management flow.
Avoid
- Storing sensitive user permissions in long-lived access tokens without revocation capabilities.
- Trusting the
algheader from untrusted incoming tokens without backend whitelisting.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 34 lines · 25 tokens per session scan A eb0438a556c7
jwt-security-hardener is a skill published in the GitHub repository codebygarv/Ai-skills (25 stars, last pushed 19d ago), licensed MIT. It adds 25 tokens to every session and 405 once invoked, about $0.0001 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 2026-09-03.
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