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 UnboundCompute/security-agent-skills --skill auditing-service-mesh-mtls-and-authz-trustgit clone --depth 1 https://github.com/UnboundCompute/security-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/unboundcompute/security-agent-skills/auditing-service-mesh-mtls-and-authz-trust)<a href="https://agentmods.dev/skills/unboundcompute/security-agent-skills/auditing-service-mesh-mtls-and-authz-trust"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/auditing-service-mesh-mtls-and-authz-trust/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/unboundcompute/security-agent-skills/auditing-service-mesh-mtls-and-authz-trust"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/auditing-service-mesh-mtls-and-authz-trust.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 | $0.00164 | $0.01970 |
| Opus 5 | $0.00082 | $0.00985 |
| Sonnet 5 | $0.00033 | $0.00394 |
| Haiku 4.5 | $0.00016 | $0.00197 |
Grade A, and why
auditing-service-mesh-mtls-and-authz-trust 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 12d 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auditing service mesh mTLS and authz trust: when the mesh asserts a trust it does not enforce
A service mesh is sold as identity and encryption between workloads: sidecars establish mutual TLS so every call is authenticated, and authorization policies decide who may call whom. Teams then reason about the cluster as if those guarantees hold everywhere. The gaps are where the guarantee is asserted but not enforced. A mesh in permissive mode accepts plaintext next to mutual TLS, so an unauthenticated caller is still served while the dashboards show encryption. Authorization frequently defaults to allow, or a policy covers some services and not the one that matters. A workload reachable outside the mesh, directly by pod IP or through an ingress that skips the sidecar, bypasses every mesh control. And an identity check that trusts a caller-set header authenticates nothing. You audit this by testing whether the mesh actually refuses an unauthenticated and an unauthorized call, rather than trusting that it does.
When to use
- A service mesh is the control enforcing mutual TLS and per-service authorization between workloads.
- The mesh may run in permissive mode, accepting plaintext alongside mutual TLS.
- Authorization policies may be missing, default-allow, narrowly scoped, or bypassable outside the sidecar.
Scope check
Test a mesh only on clusters you own or are authorized to assess, on non-production services. Probing means sending calls between real workloads, including unauthenticated ones, so keep them benign and inside the authorized namespaces. If you can't name the authorization, stop.
The loop
- Establish the intended call graph first. Name which services may call which, and that every call must be mutually authenticated. This is the false-positive killer: a mesh in strict mutual-TLS mode with authorization policies that allow exactly the intended edges and deny by default is enforcing its claim. Name the intended graph and the authentication requirement, then test against them.
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.
- 12d ago First seen · 134 lines · 164 tokens per session scan A fa678e9978d2
auditing-service-mesh-mtls-and-authz-trust is a skill published in the GitHub repository UnboundCompute/security-agent-skills (5 stars, last pushed 4d ago), licensed MIT. It adds 164 tokens to every session and 1,970 once invoked, about $0.0008 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 2026-08-31.
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