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Monolog Masker

A lightweight, zero-dependency Monolog processor to keep sensitive data and secrets out of your logs.

🛑 The Problem

When logging requests, exceptions, or context arrays, it's easy to accidentally leak sensitive information like passwords, API keys, or Personally Identifiable Information (PII) into your log files or monitoring systems (Datadog, Sentry, ELK). This can lead to security breaches and GDPR compliance issues.

✅ The Solution

monolog-masker provides a simple Processor for Monolog that recursively intercepts and masks sensitive keys before they are ever written to your logs.

📦 Installation

You can install the package via composer:

🚀 Quick start

Push the processor onto your logger. With the defaults you are protected in one line:

The processor walks message, context and extra and masks, secure by default:

• Sensitive keys — values whose key contains a known sensitive segment (password, token, api_key, authorization, …). Matching is segment-aware, so compound names like db_password, userToken or x-api-key are caught too (but not tokenizer). The whole sub-tree under a sensitive key is collapsed.
• Sensitive values — tokens that look like a secret or PII (email, IBAN, JWT, Bearer …, AWS/Google keys, PEM blocks, and Luhn-validated card numbers), wherever they appear — including the log message. Only the matched sub-string is masked, so surrounding text is preserved.
• Objects in the context are traversed too (JsonSerializable, Stringable, or public properties), so secrets carried by DTOs don't slip through unmasked.

⚙️ Configuration

Everything is wired through the fluent, immutable MaskerBuilder:

Other knobs:

• withKeyMatcher() / withValueMatcher() — replace detection entirely with your own KeyMatcherInterface / ValueMatcherInterface.
• withoutValueMatching() — key-based masking only (skip value detection).
• withoutValuePatterns(['email', 'iban']) — drop specific default value patterns by name (keeps the others and card detection).
• matchKeysExactly() — whole-string key matching instead of segment-aware (no compound-key detection, fewer false positives).
• maskMessage(false) — stop masking the log message.
• traverseObjects(false) — leave objects untouched.

Processor ordering

Monolog runs processors in reverse of their push order. To also mask the extra data added by other processors (e.g. WebProcessor), push the masker first so it runs last.

Depth limit

Recursion is bounded by maxDepth (default 16); anything deeper — and any object cycle — is replaced with [TRUNCATED] rather than traversed.

JSON inside a string value

Some logs carry a serialized payload as a string — typically the raw body of a POST request. Declare those keys with withJsonKeys() and the processor decodes the JSON, masks it recursively (same key + value rules), then re-encodes it:

• Opt-in: with no JSON keys declared the behaviour is unchanged — such a string stays an opaque leaf.
• A decodable JSON value takes precedence over a sensitive-key match, so a key that is both sensitive and declared JSON is looked into rather than collapsed. A non-decodable value (or a JSON scalar) falls back to the normal rules.
• Re-encoding normalises formatting (whitespace, escaping; an empty {} comes back as []) — the masked payload is semantically equal, not byte-identical.

Masking strategies

Both are configurable (placeholder, mask character, number of visible chars), and you can implement MaskStrategyInterface for anything else.

🎼 Symfony integration

Register the processor with the MonologBundle via the monolog.processor tag.

Heads-up: MaskerBuilder is immutable (with*() returns a new instance), so Symfony's calls: cannot configure it. Use the builder as a factory object (defaults) or a small factory class (custom config).

Defaults — one service:

Custom config — via a factory class:

Scope it to a handler or channel if needed: - { name: monolog.processor, handler: main } (or channel: app).

🧱 Architecture

The masking engine is decoupled from Monolog so it can be tested and reused on its own:

• Masker — recursive, immutable engine (never mutates its input; traverses arrays and objects; bounded by a max depth that also guards against cycles; optionally decodes/masks/re-encodes JSON held in string values via JSON keys).
• MaskingProcessor — thin Monolog adapter (ProcessorInterface).
• Matcher\* — pluggable detection: keys (KeyListMatcher, SegmentKeyMatcher) and values (RegexValueMatcher, CreditCardMatcher, ChainValueMatcher).
• Strategy\* — pluggable masking (FullMaskStrategy, PartialMaskStrategy).
• MaskerBuilder — fluent factory tying it all together with secure defaults.

✅ Development

This package follows the Tiime conventions (Docker + make):

The suite is held to 100% line & method coverage and 100% MSI (mutation score, via Infection). Both are enforced as hard gates in CI, so a weak test that executes code without actually asserting its behaviour fails the build.

On top of the example-based unit tests, the library's invariants are checked with property-based tests (innmind/black-box) — idempotence, no-leak, structure preservation, depth bounds, etc. — over hundreds of randomly generated, auto-shrinking inputs. These live in tests/Property (suite property, run via make proofs); coverage and mutation gates stay scoped to the deterministic unit suite.

📄 License

MIT — see LICENSE.