Parry-guard

A prompt injection scanner for AI coding tool hooks. It catches injection attacks, leaked secrets, and data exfiltration in tool inputs and outputs. It's built for Claude Code, and also works with Codex or any tool that runs command hooks with the same JSON input and output.

Early development: expect bugs and false positives. Tested on Linux and macOS.

Prerequisites

The ML models are gated on HuggingFace. Before installing:

1. Create an account at huggingface.co.
2. Accept the DeBERTa v3 license. All modes need it.
3. For full mode, also accept the Llama Prompt Guard 2 license. Meta has to approve it.
4. Create an access token at huggingface.co/settings/tokens.

Usage

Claude Code

Add to ~/.claude/settings.json:

With uvx:

{
  "hooks": {
    "PreToolUse": [{ "command": "uvx parry-guard hook", "timeout": 1000 }],
    "PostToolUse": [{ "command": "uvx parry-guard hook", "timeout": 5000 }],
    "UserPromptSubmit": [{ "command": "uvx parry-guard hook", "timeout": 2000 }]
  }
}

With rvx:

{
  "hooks": {
    "PreToolUse": [{ "command": "rvx parry-guard hook", "timeout": 1000 }],
    "PostToolUse": [{ "command": "rvx parry-guard hook", "timeout": 5000 }],
    "UserPromptSubmit": [{ "command": "rvx parry-guard hook", "timeout": 2000 }]
  }
}

With parry-guard on your PATH (from Nix, cargo install, or a release binary):

{
  "hooks": {
    "PreToolUse": [{ "command": "parry-guard hook", "timeout": 1000 }],
    "PostToolUse": [{ "command": "parry-guard hook", "timeout": 5000 }],
    "UserPromptSubmit": [{ "command": "parry-guard hook", "timeout": 2000 }]
  }
}

Codex

Add to ~/.codex/config.toml:

[[hooks.PreToolUse]]
matcher = "Bash|Read|Write|Edit|Glob|Grep|WebFetch|WebSearch|apply_patch|mcp__.*"

[[hooks.PreToolUse.hooks]]
type = "command"
command = "parry-guard hook"
timeout = 1

[[hooks.PostToolUse]]
matcher = "Bash|Read|WebFetch|Edit|apply_patch|mcp__.*"

[[hooks.PostToolUse.hooks]]
type = "command"
command = "parry-guard hook"
timeout = 5

[[hooks.UserPromptSubmit]]
matcher = ""

[[hooks.UserPromptSubmit.hooks]]
type = "command"
command = "parry-guard hook"
timeout = 2

Other hook runners

parry-guard hook reads one JSON payload from stdin and writes a JSON decision to stdout. Any tool with command hooks can use it, as long as it sends Claude/Codex-style fields (hook_event_name, tool_name, tool_input, tool_response, prompt) and respects block/deny responses.

Claude Code can ask you to confirm a PreToolUse call. Codex can't yet, so for Codex payloads parry-guard turns an "ask" into a block: it exits with a blocking code and prints the reason to stderr.

# Default: ONNX backend, statically linked, 5-6x faster than Candle
cargo install --path bin

# Candle backend: pure Rust, no native deps, portable
cargo install --path bin --no-default-features --features candle

# flake.nix
{
  inputs.parry.url = "github:vaporif/parry-guard";

  outputs = { parry, ... }: {
    # pass parry to your home-manager config via extraSpecialArgs, overlays, etc.
  };
}

# home-manager module
{ inputs, pkgs, config, ... }: {
  imports = [ inputs.parry.homeManagerModules.default ];

  programs.parry-guard = {
    enable = true;
    package = inputs.parry.packages.${pkgs.system}.default;  # onnx (default)
    # package = inputs.parry.packages.${pkgs.system}.candle;  # candle (pure Rust, portable, ~5-6x slower)
    hfTokenFile = config.sops.secrets.hf-token.path;
    # hfTokenCommand = "pass show huggingface/token";  # or fetch from a keychain / secret manager
    ignoreDirs = [ "/home/user/repos/trusted" ];
    # askOnNewProject = true;  # ask before monitoring new projects (default: monitor right away)
    # claudeMdThreshold = 0.9;  # ML threshold for CLAUDE.md scanning (default 0.9)

    # scanMode = "full";  # fast (default) | full | custom

    # Custom models (auto-sets scanMode to "custom")
    # models = [
    #   { repo = "ProtectAI/deberta-v3-small-prompt-injection-v2"; }
    #   { repo = "meta-llama/Llama-Prompt-Guard-2-86M"; threshold = 0.5; }
    # ];
  };
}

Setup

HuggingFace token

Set your token one of these ways (first match wins):

export HF_TOKEN="hf_..."                                   # direct value
export HF_TOKEN_COMMAND="pass show huggingface/token"      # command that prints the token
export HF_TOKEN_PATH="/path/to/token"                      # file path
# or place token at /run/secrets/hf-token-scan-injection

HF_TOKEN_COMMAND lets the token stay in a keychain or secret manager. The hook passes the command to the daemon instead of running it. The daemon runs it with sh -c (cmd /C on Windows) only when a model file isn't in the local HuggingFace cache yet, at most once per model load, and uses the trimmed stdout as the token. A cached model never runs it. The token is kept only in memory. Some examples:

export HF_TOKEN_COMMAND="security find-generic-password -s huggingface -w"  # macOS Keychain
export HF_TOKEN_COMMAND="secret-tool lookup service huggingface"            # GNOME Keyring / KWallet
export HF_TOKEN_COMMAND="op read op://Private/HuggingFace/token"            # 1Password
export HF_TOKEN_COMMAND="bw get password huggingface"                       # Bitwarden

The command runs with no stdin and must finish within 30 seconds. When it exits or times out, anything it left running in its process group is killed (Unix only). It must exit 0 with non-empty stdout. If it fails, the error and the last line of its stderr are logged, and the daemon downloads without it (hf-hub still uses a token saved by huggingface-cli login, if any). That works for public models such as the fast mode one. Gated models then fail to download, scans fail closed, and the daemon tries again on a later scan (up to 3 attempts per daemon). Because the daemon is detached, a command that waits for an interactive prompt (for example, a locked 1Password CLI) will time out. Unlock the store first or use a non-interactive credential.

Models are cached under $HF_HOME/hub (default ~/.cache/huggingface/hub). If HF_ENDPOINT is set, models are downloaded from that mirror and the token is sent to it.

With HF_TOKEN or a token file, the hook copies the token to ~/.parry-guard/.hf-token (mode 0600) so the daemon can read it. With HF_TOKEN_COMMAND, nothing is written, and the hook deletes any leftover copy when it next starts the daemon.

The daemon starts on the first scan, downloads the model on the first run, and stops after 30 idle minutes. Without Nix, set the env vars in your shell profile or pass flags (see Config).

Project scanning

By default, every new project is scanned from its first session, with no prompt. To skip a repo, run parry-guard ignore <path>.

To be asked first instead, set PARRY_ASK_ON_NEW_PROJECT=true (askOnNewProject = true in Nix). docs/opt-in-flow.md shows the full flow.

path defaults to the current directory.

What each hook does

PreToolUse runs 7 checks in order and stops at the first hit:

1. Skip ignored or unknown repos
2. Enforce taint
3. Scan CLAUDE.md
4. Block exfiltration
5. Catch destructive operations
6. Block sensitive paths
7. Scan input content for injection (Write, Edit, Bash, MCP tools)

PostToolUse scans tool output for injection and secrets. A hit taints the project.

UserPromptSubmit audits your .claude/ directory for dangerous permissions, injected commands, and hook scripts.

Daemon and cache

Hook calls start the daemon if it isn't running. You can also run it yourself with parry-guard serve --idle-timeout 1800.

Scan results are cached in ~/.parry-guard/scan-cache.redb for 30 days. A cache hit takes about 8ms, versus 70ms+ for inference. All projects share the cache, and it's pruned hourly.

Detection layers

The scanner fails closed: if it can't tell whether something is safe, it treats it as unsafe.

1. Unicode: invisible characters (PUA, unassigned codepoints), homoglyphs, RTL overrides.
2. Substring: Aho-Corasick matching for known injection phrases.
3. Secrets: 40+ regex patterns for credentials (AWS, GitHub/GitLab, cloud providers, database URIs, private keys, and more).
4. ML classification: a DeBERTa v3 model. Text is split into 256-char chunks with 25 chars of overlap, and long texts are scanned head and tail. Default threshold is 0.7.
5. Bash exfiltration: tree-sitter AST analysis for network sinks, command substitution, obfuscation (base64, hex, ROT13), DNS tunneling, cloud storage, 60+ sensitive paths, and 40+ exfil domains.
6. Script exfiltration: the same source-to-sink analysis for script files in 16 languages.

Config

Custom patterns go in parry-guard/patterns.toml under your config dir: ~/.config on Linux, ~/Library/Application Support on macOS. You can add or remove sensitive paths, exfil domains, and secret patterns. Custom models go in parry-guard/models.toml in the same dir and are used with --scan-mode custom. See examples/models.toml.

Contributing

See CONTRIBUTING.md.

Credits

• ML model: ProtectAI/deberta-v3-small-prompt-injection-v2, also used by LLM Guard
• Exfil patterns: inspired by GuardDog, Datadog's malicious package scanner
• Full scan mode optionally uses Llama Prompt Guard 2 86M by Meta, licensed under the Llama 4 Community License. Built with Llama.

License

MIT

Llama Prompt Guard 2 (used in full mode) has its own license, the Llama 4 Community License. See LICENSE-LLAMA.