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-mobile-backend-and-firebase-exposuregit 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-mobile-backend-and-firebase-exposure)<a href="https://agentmods.dev/skills/unboundcompute/security-agent-skills/auditing-mobile-backend-and-firebase-exposure"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/auditing-mobile-backend-and-firebase-exposure/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-mobile-backend-and-firebase-exposure"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/auditing-mobile-backend-and-firebase-exposure.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 | $0.00192 | $0.02102 |
| Opus 5.5 | $0.00077 | $0.00841 |
| Sonnet 5.5 | $0.00038 | $0.00420 |
| Haiku 4.5 | $0.00019 | $0.00210 |
Grade A, and why
auditing-mobile-backend-and-firebase-exposure 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 1mo 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auditing mobile backend and Firebase exposure: when the server trusts the app to say no
A mobile app usually talks to a hosted backend, a mobile-backend service, a cloud datastore, a storage bucket, or a set of cloud functions, and it is easy to build that backend as though the app were the only client. The app checks what the user may see and calls the backend accordingly, so the backend rules are left permissive because the app is trusted to enforce access. But the app is not the only client: anyone can take the app's credentials and endpoints and call the backend directly, skipping every check the app performs. When the backend authorizes by rules that are too broad, by values the client sets, or by the assumption that only the genuine app calls it, a direct request reads or writes another user's data, invokes a privileged operation, or reaches records the user should never see. The bug is authorization that lives in the client while the backend serves whoever asks. You audit these by calling the backend directly and checking whether the server, not the app, enforces access.
When to use
- A mobile app uses a hosted backend, datastore, storage bucket, or cloud functions you can call directly.
- The backend's access rules or operations may authorize by client-set values or assume only the app calls.
- Datastore rules or storage permissions may be permissive enough to serve another user's data.
Scope check
Audit backend exposure only on services you own or are authorized to assess, on non-production or test projects with test accounts, reading and writing only your own test data when you exercise a rule directly. A confirmed gap reaches other users' data or privileged actions, so keep every probe within scope and prefer an isolated project. If you can't name the authorization, stop.
The loop
- Establish whether the backend enforces authorization itself or trusts the app first. For each backend operation and datastore path, determine whether the server authorizes the request against the authenticated caller and its own rules, or whether it relies on the app to have checked and serves any direct request. This is the false-positive killer: a backend whose rules restrict every read and write to the entitled caller cannot be bypassed by calling it directly, whatever the app does. Name where authorization is enforced before crafting a direct request.
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.
- 1mo ago First seen · 139 lines · 192 tokens per session scan A 5f57ecb32279
auditing-mobile-backend-and-firebase-exposure is a skill published in the GitHub repository UnboundCompute/security-agent-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 192 tokens to every session and 2,102 once invoked, about $0.0008 per session on Opus 5.5. 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 2026-09-09.
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