Borrowing it
Nothing to install: this file belongs to LedgerHQ/ledger-live. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/LedgerHQ/ledger-live/develop/.agents/skills/detect-data-leaks/SKILL.mdgit clone --depth 1 https://github.com/LedgerHQ/ledger-liveWrote 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/ledgerhq/ledger-live/detect-data-leaks)<a href="https://agentmods.dev/skills/ledgerhq/ledger-live/detect-data-leaks"><img src="https://agentmods.dev/badge/skills/ledgerhq/ledger-live/detect-data-leaks/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/ledgerhq/ledger-live/detect-data-leaks"><img src="https://agentmods.dev/badge/skills/ledgerhq/ledger-live/detect-data-leaks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 120 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00030 | $0.01812 |
| Opus 5.5 | $0.00012 | $0.00725 |
| Sonnet 5.5 | $0.00006 | $0.00362 |
| Haiku 4.5 | $0.00003 | $0.00181 |
Grade A, and why
detect-data-leaks 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 yesterday.
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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scope — what is PII, what is NOT
We only consider PII that is sent to third-party services. Any call to our own backend with PII is not considered a data leak.
Every third-party service should be considered, but each has a different risk level. Logging services are the highest risk.
Some information is only PII in context — for example, public addresses are not PII by themselves, but on a logging service such as Datadog, an address can be linked to a location and device, allowing identification of the person behind it.
Crash reports need to be studied alongside logs — they are a common source of data leaks.
Any service that queries the blockchain for an address is not a concern — the query is mandatory for the system to function and the data is not linked to any other identifiable information. This applies to all coin modules. Examples:
- Kaspa →
api.kaspa.org - EVM (Ethereum, BSC, Polygon…) → Etherscan-family
- Tron → TronGrid (
api.trongrid.io)
Known third-party sinks in this repo
Prioritize these, but do not exclude others:
- Datadog
- Sentry
- Mixpanel
Analytics also leave from the monorepo layers (shared/, domain/, features/, devtools/), not only the apps:
@shared/analyticsownstrack()andtrackPage();@shared/analytics-reactwraps them in<Track>and<TrackScreen>(universal, web and native). The apps plug their vendor (setAnalytics) and filters into this pipeline, so a layer call reaches the same vendor as an app call.- Feature packages send events either through those functions (
@features/flow-fear-and-greed, and@features/platform-pay-analytics, which buildscreatePayAnalyticsHelperon@shared/analytics'strack) or through an adapter the app injects (createContactsAnalyticsHelperin@features/flow-contacts). For an injected adapter, read the app side that builds it: that is where the payload reaches the vendor. @features/platform-coin-observabilitydecides when coin errors reach Datadog.
High-risk variables
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.
- yesterday Changed · +19 lines 72e1627221aa
- 26d ago Changed 0363e36668d4
- 2mo ago First seen · 121 lines · 30 tokens per session scan A 245e0f620036
detect-data-leaks is a skill published in the GitHub repository LedgerHQ/ledger-live (624 stars, last pushed yesterday), licensed MIT. It adds 30 tokens to every session and 1,812 once invoked, about $0.0001 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 2026-08-30.
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