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Security depth
- Data-exfiltration technique detection (opt-in under security.dlp): DNS
exfil, secret-file piped to network, command-substituted uploads. Names
the technique, never the data; conservative/high-signal.
- `burnwall security --summary`: a "what Burnwall caught" receipt grouped by
type, so passive protection registers as ongoing value.
- MCP firewall validated against the published attacks (Invariant tool-
poisoning/SSH exfil, MCPoison rug-pull, <IMPORTANT> shadowing) as a test
corpus.
Governance
- `burnwall audit pack`: one-command evidence bundle (signed receipts +
CycloneDX 1.6 AIBOM + SARIF 2.1.0 + a MANIFEST mapping artifacts to ISO
42001 / EU AI Act / FINRA).
Docs
- README: Trust & privacy, defense-in-depth framing, and the built-in
mcp-watch firewall in the MCP scope note.
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@@ -123,11 +123,21 @@ Every API call flows through Burnwall:
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Responses are **never modified** — Burnwall reads them, logs the cost, and passes them through unchanged.
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### Defense-in-depth, not a silver bullet
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Security rules are evaluated **before the request leaves your machine** — a
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blocked request never reaches the provider. That's the point: it's another layer
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that holds even when a tool's own approval prompt, allowlist, or sandbox is
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bypassed (and those have been, repeatedly). Burnwall doesn't claim you're under
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attack; it claims that *if* a prompt-injected agent tries to read `~/.ssh` or
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pipe a secret to the network, the rule fires locally first. Pair it with your
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tool's native controls — it's designed to complement them, not replace them.
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## Scope: What Burnwall Guards
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Burnwall sits on the **LLM API path** — the HTTP traffic between your AI tool and Anthropic/OpenAI. Security scanning, budget enforcement, and cost tracking all operate on that traffic.
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It does **not**intercept **MCP** (Model Context Protocol) traffic. When your agent calls an MCP server's tools, that traffic flows through your AI tool directly — Burnwall never sees it, so it can't scan or block it. MCP-layer protection is a separate concern; dedicated MCP-firewall tools exist and run cleanly alongside Burnwall.
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The LLM-path proxy does **not**automatically see **MCP** (Model Context Protocol) traffic — that flows from your AI tool to MCP servers directly. For that layer, Burnwall ships a dedicated **MCP firewall** you put in front of your MCP servers (`burnwall mcp-watch`): it detects tool-poisoning and "rug-pull" (silent post-approval redefinition) attacks and enforces an approval workflow. Run it alongside the main proxy for end-to-end coverage.
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## Supported Tools
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Cache savings today: $47.82
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```
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## Privacy
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## Trust & privacy
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Burnwall sits in your API traffic path, so it earns that position by being
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verifiable, not by asking for trust:
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-**100% local.** No data ever leaves your machine (except API forwarding).
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-**100% local.** No data ever leaves your machine except the API forwarding you
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asked for. Works offline (apart from the forwarding itself).
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-**Zero telemetry.** No analytics, no phone-home, no tracking. Ever.
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-**No prompt logging.** Only metadata is stored (model, tokens, cost, timestamp).
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-**No API key storage.** Keys pass through in headers and are never written to disk.
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-**Open source.** Audit the code yourself.
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-**Read-only on responses.** Burnwall inspects responses to compute cost and
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**never modifies them** — your tool gets the provider's bytes unchanged.
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-**Single binary, signed releases.** Install from a checksummed, signed release
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(or `cargo install` from source). No background services you didn't ask for.
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-**Open source.** The "no network calls except forwarding" claim is auditable —
All artifacts are metadata only — no prompt content, no API keys.\n\
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Verify the receipt chain at any time with `burnwall audit verify`.\n\
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\n\
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## Artifacts → controls\n\
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\n\
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| File | What it is | Maps to |\n\
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|------|-----------|---------|\n\
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| `receipts.json` | Ed25519 hash-chained, tamper-evident log of every forwarded/blocked AI action (model, timestamp, action, cost). | EU AI Act Art. 12 (record-keeping) & Art. 26 (deployer logs); FINRA prompt/output-log & model-version expectations; ISO/IEC 42001 operational logging. |\n\
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| `aibom.cdx.json` | CycloneDX 1.6 AI Bill of Materials — models used (as ML-model components), MCP tools/services, and window totals. | ISO/IEC 42001 AI-system inventory & model lineage; AIBOM / SBOM-for-AI procurement requirements; EU AI Act technical documentation. |\n\
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| `security.sarif.json` | SARIF 2.1.0 record of blocked attempts (denied paths/commands, secrets, exfiltration). | Evidence of active guardrails / data-egress control; ingestible by GitHub code scanning and SIEMs. |\n\
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\n\
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> Mapping is provided to help a reviewer locate evidence; it is not a\n\
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> certification or legal attestation. Confirm scope against your own\n\
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