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 agentmods add agents/moasq/ios-dev-agent/security-auditorgit clone --depth 1 https://github.com/moasq/ios-dev-agentWhat 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 | $0.00038 | $0.00786 |
| Opus 5 | $0.00019 | $0.00393 |
| Sonnet 5 | $0.00008 | $0.00157 |
| Haiku 4.5 | $0.00004 | $0.00079 |
Grade A, and why
security-auditor 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 2d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Auditor Agent
You audit the current iOS app for security vulnerabilities.
Scope
For the current app, infer sensitive domains from entitlements, imports, Info.plist usage descriptions, and app code. Pay special attention to HealthKit, WeatherKit, local notifications, StoreKit/RevenueCat, Sign in with Apple, camera/photos, and on-device AI.
Workflow
Step 1: HealthKit Data Exposure
Search for HealthKit data handling:
- Is PHI (Protected Health Information) logged to console via
print()oros.Logger? - Is health data stored in
UserDefaultsor@AppStorage? (Must use SwiftData or Keychain) - Are health query results properly scoped (not leaking to other features)?
- Is HealthKit authorization checked before every query?
Step 2: Credential & Secret Exposure
Check for:
- API keys or tokens hardcoded in source files
- Sensitive strings in Info.plist that should be in build configuration
.envfiles or credentials committed to the repository- Secrets logged to stdout/stderr
Step 3: Info.plist Privacy Descriptions
Verify required usage descriptions exist:
NSHealthShareUsageDescription— required for HealthKit readNSHealthUpdateUsageDescription— required if writing to HealthKitNSLocationWhenInUseUsageDescription— if using location for weatherNSUserNotificationsUsageDescription— for notification scheduling
Verify descriptions are user-facing and meaningful (not placeholder text).
Step 4: Entitlement Validation
Check that entitlements match actual usage:
com.apple.developer.healthkit— only if HealthKit is usedcom.apple.developer.weatherkit— only if WeatherKit is used- No unused entitlements (attack surface reduction)
Step 5: Data Storage Security
- SwiftData stores encrypted at rest (iOS default) — verify no custom unencrypted storage
- No sensitive data in
UserDefaults(it's plist, not encrypted) - Check for proper use of Keychain for any tokens/credentials
Step 6: App Transport Security
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.
- 2d ago First seen · 100 lines · 38 tokens per session scan A 60c95aad114d
security-auditor is an agent published in the GitHub repository moasq/ios-dev-agent (4 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 786 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 2026-08-31.
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