PROMPTPurify: 14 MB CPU-only prompt-injection guard (benchmarked vs. OSS guard)
PROMPTPurify is a lightweight, CPU-only prompt-injection guard designed for LLM chat applications. It offers a small installation size and operates without the need for GPUs or additional services. Developed by SecureLayer7, it aims to provide a more efficient alternative to existing open-source guardrails.
- ▪PROMPTPurify has an installation size of approximately 14 MB and runs on CPU only.
- ▪It is designed to be a drop-in guard between user input and LLMs, functioning on the same machine without requiring external services.
- ▪The model was built from scratch to achieve a favorable size and latency tradeoff, and it is MIT-licensed for use in production.
Hacker News (Newest) files mainly under programming. We currently carry 5,306 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/securelayer7/PROMPTPurify |
| Publication time | Sat, 30 May 2026 04:34:34 +0000 |
| Retrieval time | 2026-05-30T04:41:57.269Z |
| Last seen | 2026-05-30T04:41:57.269Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | hLGdwBl4JvZN |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
promptpurify Tiny prompt-injection firewall for LLM chat apps. ~14 MB. CPU-only. Drop-in guard between your user input and your LLM — runs on the same box, no GPU, no API, no extra service. Built by the SecureLayer7 red-team. Most OSS guardrails are hundreds of MB, want a GPU, and still miss the attacks we see in production. We needed something we could ship inside our own AI products and our customers' apps without any of that. Why this exists promptpurify typical OSS guardrail Install size ~14 MB ONNX 180 MB – 7 GB Inference CPU, single-digit ms GPU recommended Where it runs In your Node process Sidecar or hosted API Cost per call $0 $ or GPU compute Benchmark comparison vs OSS baselines → docs/BENCHMARKS.md.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.