# Security.txt & Well-Known Policy Auditor (`quanmatrix/well-known-securitytxt-auditor`) Actor

Check public websites for RFC 9116 security.txt discovery, HTTPS placement, contact details, expiry signals and structured security-policy hygiene findings.

- **URL**: https://apify.com/quanmatrix/well-known-securitytxt-auditor.md
- **Developed by:** [Rafael Barreto Haddad](https://apify.com/quanmatrix) (community)
- **Categories:** Developer tools, Automation
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.85 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Security.txt & Well-Known Policy Auditor

Check public websites for RFC 9116 security.txt discovery, HTTPS placement, contact details, expiry signals and structured security-policy hygiene findings.

### Why use this Actor

Security and asset teams need recurring evidence that vulnerability-disclosure and security-related /.well-known endpoints remain discoverable, current and consistent across website portfolios.

### Key features

- Buyer-native inputs aligned to **well-known policy**.
- Predictable structured output in the default Apify Dataset.
- Pay Per Event pricing tied to measurable result rows or reports.
- Optional MCP connector delivery for downstream automation and AI agents.

### Quick start

Start with this working example and replace the target values with your own:

```json
{
  "urls": [
    "https://www.google.com",
    "https://github.com"
  ]
}
```

The Actor writes structured results to the default Apify Dataset and can be used from the Store, API, schedules, Tasks, automations and MCP-compatible AI workflows.

### Input

- `urls` — Websites: Public sites to audit for RFC 9116 security.txt policy.
- `previousSnapshots` — Previous policy snapshots: Optional prior snapshots keyed by input or final URL for drift detection.
- `failRunOnRisk` — Fail run on material policy risk: Fail after writing evidence when a policy is missing, expired, or regresses.
- `maxUrls` — Maximum websites: Configure Maximum websites for this Actor run.

All integration and advanced analysis fields are optional. The default example is intentionally runnable without configuring MCP or a previous-run baseline.

### Output

The Dataset exposes predictable machine-readable output. Representative fields include `dataset`.

### Pricing

This Actor uses Pay Per Event. The current factory base price is **$0.001000 per result event**. The Apify Store remains the source of truth for the price and plan/tier details shown to the buyer.

### Use cases

- Run the buyer-ready workflows exposed as Apify Tasks without preparing a custom integration first.
- Use the Actor from API or schedules for recurring collection, comparison or monitoring.
- Feed the structured Dataset output into spreadsheets, databases, automations or AI agents.
- Compare repeat runs when the product supports snapshots or previous-run inputs.

### Automation and AI

Use the same Actor through Apify API, schedules, public Tasks and the Apify MCP server. Outputs are structured for downstream workflows and AI agents rather than requiring manual copy/paste.

### Limitations

- Public websites and upstream APIs can change markup, access rules, rate limits or field availability without notice.
- Fields that are not publicly available are returned as unavailable or omitted rather than fabricated.
- Analytical outputs depend on the quality and coverage of the supplied or collected source data.
- Treat marketplace, reputation, workforce, safety or commercial signals as decision support and validate material decisions against the underlying source evidence.

### Detailed documentation

### Detailed documentation

Audit public websites for RFC 9116 vulnerability-disclosure policy health, expiry, discoverability, and change evidence.

### Why use this Actor

A security.txt file is small, but it is operationally important. Security teams, agencies, asset owners, and vendor-risk programs need to know whether a public vulnerability-disclosure contact exists, whether the policy is still current, whether it is published at the preferred well-known path, and whether a deployment or domain migration silently changed it. This Actor turns those checks into deterministic structured evidence that can be scheduled, compared, exported, and consumed by CI or agent workflows.

### Key features

- Checks `/.well-known/security.txt` first and supports the legacy `/security.txt` location.
- Parses Contact, Expires, Canonical, Policy, Encryption, Preferred-Languages and related RFC-style fields.
- Validates expiry and calculates days remaining until expiration.
- Distinguishes missing, legacy-only, expired, incomplete, and healthy policy states.
- Emits a reusable normalized policy snapshot and SHA-based fingerprint.
- Compares an optional previous snapshot and reports exact changed fields and regression state.
- Supports a fail-after-evidence gate for CI/CD or scheduled policy monitoring.
- Rejects private, loopback, link-local, reserved, and otherwise unsafe destinations.

### Input

Provide a `urls` array containing public HTTP or HTTPS websites. Optional `previousSnapshots` may be keyed by the original or final URL. Set `failRunOnRisk` when a workflow should fail after evidence is stored if a material policy problem is detected. `maxUrls` bounds batch size.

### Output

Each result includes the final URL, status, score, discovered location, contacts, expiration date, days to expiry, Canonical/Policy/Encryption metadata, fingerprint, changed fields, regression flag, issue codes, and an `agentAction` suitable for automation.

### Example

```json
{
  "urls": ["https://github.com"],
  "previousSnapshots": {},
  "failRunOnRisk": false,
  "maxUrls": 100
}
```

A healthy result can return `score: 100`, `location: "well-known"`, parsed contact methods, an expiry horizon, and `agentAction: "MONITOR"`.

### Use cases

- Vulnerability disclosure program QA.
- Domain and attack-surface inventories.
- Vendor-risk and supplier evidence collection.
- Scheduled expiry monitoring.
- Website migration and release regression checks.
- Agency portfolio audits.

### Pricing

Billing is pay per successfully audited result. There is no separate external security API or AI service required by the Actor.

### Limitations

This Actor audits observable public security.txt metadata. It does not test whether a security team responds to reports, does not verify organizational ownership, and does not perform penetration testing or vulnerability discovery. Network failures and upstream blocking are returned as explicit evidence rather than hidden.

### Privacy and permissions

Only public HTTP(S) targets are accepted. Private and reserved network destinations are rejected before requests are made. The Actor reads public policy text and does not request credentials or private security reports.

#### Input reliability — 25 October 2026

Target lists are validated before network work, trimmed and deduplicated. Empty lists and malformed baselines are rejected rather than silently auditing a default website. Exact duplicate targets produce one result. Existing output fields and prices are preserved.

- 2026-10-25: parse lowercase UTC z expiry timestamps; flag invalid expiry dates instead of awarding a clean score.

# Changelog

This Actor's version history is a separate document: https://apify.com/quanmatrix/well-known-securitytxt-auditor/changelog.md

# Actor input Schema

## `urls` (type: `array`):

Public sites to audit for RFC 9116 security.txt policy. Exact duplicates are processed once; empty target arrays are rejected.

## `previousSnapshots` (type: `object`):

Optional prior snapshots keyed by input or final URL for drift detection.

## `failRunOnRisk` (type: `boolean`):

Fail after writing evidence when a policy is missing, expired, or regresses.

## `maxUrls` (type: `integer`):

Configure Maximum websites for this Actor run.

## `mcpConnectors` (type: `array`):

Optional MCP connectors authorized in your Apify account. Use them to send or write this Actor result to tools such as Slack, Notion, GitHub, Sentry, Supabase, or another compatible MCP service.

## `mcpToolName` (type: `string`):

Optional exact MCP tool name. Leave blank to let the selected MCP action preset discover a compatible tool automatically.

## `mcpToolArguments` (type: `object`):

JSON object passed to the selected MCP tool. String values may use {{actor_title}}, {{result_summary}}, or {{result_json}} placeholders.

## `mcpFailOnError` (type: `boolean`):

When enabled, an MCP delivery error fails the Actor run. Disabled by default so data extraction and intelligence results remain available even if the external destination is unavailable.

## `mcpActionPreset` (type: `string`):

Choose a safe action pattern. AUTO_SAFE_WRITE discovers a compatible non-destructive write tool automatically; use a specific preset for Slack, GitHub, Notion, or database delivery.

## Actor input object example

```json
{
  "urls": [
    "https://github.com"
  ],
  "previousSnapshots": {},
  "failRunOnRisk": false,
  "maxUrls": 100,
  "mcpToolName": "",
  "mcpToolArguments": {},
  "mcpFailOnError": false,
  "mcpActionPreset": "AUTO_SAFE_WRITE"
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("quanmatrix/well-known-securitytxt-auditor").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("quanmatrix/well-known-securitytxt-auditor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call quanmatrix/well-known-securitytxt-auditor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,quanmatrix/well-known-securitytxt-auditor"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/m2WaBAYC2bbODNmEs/builds/8ehys77kKxEcBerIA/openapi.json