# fermata

**A fast, harness-agnostic security layer for AI coding agents.**

AI coding agents read files, run commands, and inspect output as part of their normal workflow. When they read `.env`, secret values get tokenized into the LLM's context window -- and from there they can leak into commits, PR descriptions, log messages, or API calls. No AI coding agent ships built-in post-read secret filtering today. fermata fixes that.

## Why

Traditional security blocks the file and hopes the agent doesn't find the data through another path. This is insufficient -- secrets appear in shell output, log files, error messages, and indirect reads that bypass any access-control list.

fermata operates on two independent levels:

- **Policy gate** (PreToolUse) -- `.botignore` blocks reads, writes, and dangerous commands before they execute. Catches ~90% of accidental secret access.
- **Secret filtering** (PostToolUse) -- `.botsecrets` redacts secret *values* from tool output before they enter the LLM context. Catches the remaining cases regardless of how secrets appear.

The key insight: blocking a file is necessary but not sufficient. The agent can have read access to `.env` without secret values being revealed -- if the output is redacted before it reaches the model.

## Quick Start

### Install

```bash
cargo install --path . --features cli
```

### Protect a project in 30 seconds

```bash
# Block direct access to secret files
echo ".env" > .botignore

# Declare where secrets live -- fermata parses them and redacts values
cat > .botsecrets << 'EOF'
[files]
patterns = [".env", ".env.*", "secrets.*"]
EOF
```

### Wire into Claude Code

Add both hooks in `.claude/settings.json`:

```json
{
  "hooks": {
    "PreToolUse": [
      {
        "matcher": "Bash|Read|Edit|Write",
        "hooks": [
          { "type": "command", "command": "fermata hook --harness claude" }
        ]
      }
    ],
    "PostToolUse": [
      {
        "matcher": "Bash|Read|Edit|Write",
        "hooks": [
          { "type": "command", "command": "fermata hook --harness claude --event post-tool-use" }
        ]
      }
    ]
  }
}
```

That's it. PreToolUse blocks forbidden operations. PostToolUse redacts secret values from tool output before they reach the LLM.

## How It Works

fermata interposes on every tool call in the agent's lifecycle:

```
Agent wants to run a tool
        |
   PreToolUse ── fermata checks .botignore / botignore.toml
        |            blocked? → deny with reason
        |            allowed? ↓
   Tool executes
        |
   PostToolUse ── fermata scans output for secret values
        |            found? → replace with ***** before LLM sees it
        |
   Clean output enters LLM context
```

Three layers of defense, each independent:

| Layer | Mechanism | What it catches |
|-------|-----------|-----------------|
| **Access control** | `.botignore` rules block tool calls by path | Direct reads/writes to sensitive files |
| **Known-value redaction** | `.botsecrets` declares secret files; fermata parses them and builds an Aho-Corasick automaton | Every occurrence of a declared secret value, in any tool output, regardless of source |
| **Heuristic detection** | Regex patterns from gitleaks detect undeclared secrets (AWS keys, JWTs, GitHub PATs, database URLs) | Secrets not covered by the manifest -- runtime-generated, unexpected locations |

Performance: ~1-5ms per tool call. Cold start (loading config + parsing secret files) is ~10-20ms.

## Configuration

Three files, each optional, each solving a different problem:

### `.botignore` -- the 80% case

Gitignore syntax. Blocks both reads and writes. Onboarding is one line.

```gitignore
.env
.env.*
secrets/**
```

### `botignore.toml` -- per-operation rules

Separate namespaces so the same file can be readable but not writable:

```toml
[read]
patterns = [".env*", "secrets/**"]

[write]
patterns = ["vendor/**", "*.lock"]

[bash]
deny = ["rm -rf /", "curl * | sh"]
```

### `.botsecrets` -- secret value redaction

Declares which files contain secrets. fermata parses them, extracts values, and redacts every occurrence in tool output.

```toml
[files]
patterns = [".env", ".env.*", "secrets.*"]

[keys]
include = ["STRIPE_*", "MY_APP_SIGNING_*"]

[heuristic]
enabled = true
```

Built-in key patterns (`*_KEY`, `*_SECRET`, `*_PASSWORD`, `*_TOKEN`, `DATABASE_URL`, etc.) handle most projects without custom configuration.

See [docs/configuration.md](docs/configuration.md) for the full reference.

## Commands

```bash
# Check if a path is allowed
fermata check --op read /path/to/.env     # exit 1 = blocked
fermata check --op write src/main.rs       # exit 0 = allowed

# Run as a hook (reads harness JSON from stdin)
fermata hook --harness claude
fermata hook --harness claude --event post-tool-use
```

See [docs/commands.md](docs/commands.md) for the full CLI reference.

## Library API

fermata is also a Rust library:

```rust
use dirigent_fermata::core::secrets::{Manifest, Redactor, Scanner, SecretsConfig};

// Load .botsecrets and build the redaction manifest
let config = SecretsConfig::load("/path/to/project")?;
let manifest = Manifest::discover(&config)?;

// Known-value redaction (Aho-Corasick, sub-millisecond)
let redactor = Redactor::from_manifest(&manifest);
let clean = redactor.redact("DB_PASSWORD=hunter2");
// -> "DB_PASSWORD=*****"

// Heuristic scanning (regex patterns)
let scanner = Scanner::new(&config);
let findings = scanner.scan("Found key: AKIA1234567890ABCDEF");
// -> [Finding { pattern: "AWS Access Key", confidence: High, .. }]
```

## Security Model

fermata addresses a novel security concern: **reveal** -- whether secret *values* enter the LLM context. Traditional file-level access control operates on file identity (which file). Secret redaction operates on data content (which values). The reveal problem can only be solved at the data-content level.

Read [docs/security-model.md](docs/security-model.md) for the full analysis, including the Reveal Triangle and defense-in-depth architecture.

## Threat Model

fermata is a heuristic guard, not a sandbox. It defends against statistical agent behavior and prompt-driven mistakes -- not a deliberate adversary. This is a strength: the threat model is well-defined, and the boundaries are documented honestly.

Read [docs/threat-model.md](docs/threat-model.md) for what fermata catches, what it doesn't, and what to combine it with.

## Harness Support

| Harness | Status | Mechanism |
|---------|--------|-----------|
| Claude Code | Shipped | PreToolUse + PostToolUse hooks |
| Codex CLI | Planned | Pre-exec hook adapter |
| Gemini CLI | Planned | MCP server mode |
| Any MCP agent | Planned | MCP proxy wrapping existing servers |

The policy engine and redaction logic are identical across all modes. Only the I/O adapter changes.

## Status

v0.2 -- policy gate and secret filtering engine are production-ready. All core components are implemented and tested:

- `.botignore` walker with gitignore semantics
- `botignore.toml` with read/write/bash namespaces
- Claude Code PreToolUse and PostToolUse adapters
- `.botsecrets` config, manifest discovery, multi-format parser (.env, TOML, YAML, JSON)
- Aho-Corasick known-value redactor
- Heuristic scanner with gitleaks-derived patterns

## The `.botsecrets` Vision

`.botsecrets` is designed to be the **`.gitignore` of AI agent security**: a simple, declarative, human-readable file that every project can drop in to protect its secrets from AI agents.

The format is harness-agnostic from day one. It declares *what* to protect, not *how*. The same `.botsecrets` works with Claude Code, Codex, Gemini, and any future harness that supports tool lifecycle hooks.

## License

Licensed under either of [Apache License, Version 2.0](LICENSE-APACHE) or [MIT License](LICENSE-MIT) at your option.