Datasets:

eulogik
/

suraksha-guard-38k

license: apache-2.0
language:
  - en
  - hi
tags:
  - guardrails
  - prompt-injection
  - jailbreak
  - pii
  - mcp
  - hinglish
  - synthetic
task_categories:
  - text-classification

suraksha-guard-38k: frozen guard training data (English + Hinglish + Hindi)

Guard mix behind SURAKSHA 450M by Eulogik. Template-generated with ground truth by construction: tool-risk labels come from the generated tool JSON, injection labels come from the template. No LLM-judge labeling. Code: github.com/eulogik/suraksha.

Files

guard_train.jsonl: 24,252 unique rows (deduplicated from 38,000 generated).
guard_test.jsonl: 3,058 unique rows, disjoint templates, unseen tools, unseen exfil domains.
SHA256SUMS, LICENSES.json: freeze bundle pinned before training.

Row shape: {state, questions, expected, labels, split}. Prompt rows carry prompt_injection (bool) plus severity (0-2). Tool rows carry tool_risk (safe/write/privileged/exfiltrate) plus severity.

Coverage

English plus Roman Hinglish plus Devanagari plus code-switch. PII is synthetic only (faker-style PAN/Aadhaar/phone/keys, plain plus split plus redacted plus base64). No verbatim real PII. Test tools (shell_exec, db_query, send_email, upload_file) never appear in train. Test domains never appear in train.

License

Apache-2.0 (ours, synthetic). Banking77 rehearsal rows used in training are PolyAI CC-BY-4.0 and live outside this dataset.

Keywords: guardrails dataset, prompt injection data, hinglish dataset, mcp tool risk data, synthetic security data.