/**
 * HackAPrompt Corpus Loader
 *
 * Reads the HackAPrompt-format sample JSON (text/category/label/source/language)
 * produced by scripts/hackaprompt-to-corpus.py and converts each row into the
 * CorpusSample shape used by the ATR eval harness.
 *
 * HackAPrompt is an all-adversarial corpus: every sample is an attempt to
 * subvert the system prompt. We therefore only measure recall against this
 * dataset; precision/FP rate is undefined here. For combined precision+recall
 * use this corpus alongside a benign source (PINT, real-traffic).
 *
 * @module agent-threat-rules/eval/hackaprompt-corpus
 */
import type { CorpusSample } from './corpus.js';
/**
 * The two groups breakdown.by_category reports. HackAPrompt's `correct` field
 * records whether the submission made its target model produce the level's
 * target output, i.e. whether the attack succeeded in the competition. It is
 * not an attack type. The corpus file's own `category` ("jailbreak" /
 * "prompt-injection") is a label PR #51 derived from that same field; it stays
 * in the file so the corpus keeps the digest the manifest pins, and is not used.
 */
export declare const HACKAPROMPT_OUTCOME_CATEGORY: {
    readonly succeeded: "competition-outcome:succeeded";
    readonly failed: "competition-outcome:failed";
};
export declare function loadHackaPromptCorpus(dataPath: string): readonly CorpusSample[];
export declare function getHackaPromptCorpusStats(corpus: readonly CorpusSample[]): {
    total: number;
    attacks: number;
    benign: number;
    byCategory: Record<string, number>;
    byDifficulty: Record<string, number>;
};
//# sourceMappingURL=hackaprompt-corpus.d.ts.map