Excise vs Philter

Excise is a free, open-source PDF editor for Windows, macOS, and Linux. Its central feature is permanent redaction: it removes text, images, and vector graphics from PDF content rather than placing a visible cover over them. By default, the cleanup also removes metadata, attachments, JavaScript, thumbnails, and hidden layers, and reports those removals. The app handles search, text selection and copying, annotations, page organization, Bates numbering, file-size reduction, and AcroForm filling, flattening, and creation. Its command-line tools support batch work and stable JSON output; `unredact` checks for leaked redacted text, while `audit` looks for text beneath opaque overlays. Excise reads and writes AES-128 and AES-256 encryption and inspects digital signatures against the operating system trust store. Signature inspection does not check revocation or evaluate timestamp and long-term validation material. Dynamic XFA layouts are experimental and cannot be filled. Downloads include packages for Apple Silicon macOS, Windows 10/11 x64, Ubuntu/Debian, and x64 or ARM64 Linux; builds are unsigned, not notarized, and lack auto-update.

Philter is open-source software for finding and redacting personally identifiable information and protected health information in text. For detected entities, users can choose to mask, encrypt, replace with synthetic values, remove, or pass them through. Policies, custom dictionaries, and identifier patterns such as medical record numbers and transaction IDs let teams configure what to detect and how to handle it. General Purpose, Healthcare, and COVID-19 NLP lenses address different types of text. Philter provides an HTTP REST API, a Java SDK, and an OpenAPI specification for generating clients in other languages. It can run in a private environment or through AWS, Google Cloud, and Microsoft Azure marketplaces. The maker says text stays in the customer’s environment, including firewalled or air-gapped deployments. Redaction requests are recorded in a tamper-evident, hash-chained audit log that can be queried and exported to CSV. Detection is probabilistic, so results should be checked against an organization’s own data before production use. The open-source toolkit has community support; commercial licenses include direct support.