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 RedHatProductSecurity/prodsec-skills --skill authentication-enforcementgit clone --depth 1 https://github.com/RedHatProductSecurity/prodsec-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/redhatproductsecurity/prodsec-skills/authentication-enforcement)<a href="https://agentmods.dev/skills/redhatproductsecurity/prodsec-skills/authentication-enforcement"><img src="https://agentmods.dev/badge/skills/redhatproductsecurity/prodsec-skills/authentication-enforcement/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/redhatproductsecurity/prodsec-skills/authentication-enforcement"><img src="https://agentmods.dev/badge/skills/redhatproductsecurity/prodsec-skills/authentication-enforcement.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 | $0.00041 | $0.00477 |
| Opus 5 | $0.00020 | $0.00238 |
| Sonnet 5 | $0.00008 | $0.00095 |
| Haiku 4.5 | $0.00004 | $0.00048 |
Grade A, and why
authentication-enforcement 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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Authentication Enforcement at the API Gateway
Security Requirement
AI model APIs MUST require that all principals (humans and applications) are identified, authenticated, and authorized before requests reach the models. The API gateway is the primary enforcement point for this control.
AI software MUST implement a robust standard authentication mechanism or require integration with an identity provider by default. Reducing this security posture should only be an option the user explicitly chooses, never the default.
What Is Not Acceptable as Default
- No authentication at all (even for internal-only APIs)
- A single shared API key for all users
- An empty API key
- API key-only authentication without IdP integration
These approaches may seem to "facilitate use" but are not acceptable for cloud services and should not be the default for products.
Required Controls
| Control | Details |
|---|---|
| Authentication | Standard protocol (OAuth 2.1/OIDC) via IdP integration |
| Authorization | Verify the authenticated principal has permission for the requested operation |
| Identity | Every request must be attributable to a specific principal |
Architectures Without an API Gateway
If the AI software architecture or platform does not include an API gateway, these security controls MUST be implemented by other components:
- Check if the inference engine has standard, well-known authentication mechanisms
- Verify the inference engine can identify and authenticate principals securely
- Ensure rate limiting and input validation are handled at the inference engine level
- Document the compensating controls and their limitations
Implementation Checklist
- Deploy an API gateway in front of all AI model endpoints
- Configure the API gateway to require authentication by default
- Integrate with an OIDC Identity Provider for authentication
- Implement authorization checks based on principal identity
- Ensure every request is logged with the authenticated principal's identity
- If no API gateway: verify inference engine implements equivalent controls
- Verify that the default configuration requires authentication (not opt-in)
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 · 51 lines · 41 tokens per session scan A ce4d15e55340
authentication-enforcement is a skill published in the GitHub repository RedHatProductSecurity/prodsec-skills (52 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 41 tokens to every session and 477 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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