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* feat(worker): record token, cache, and turn usage per agent * feat: replace model tiers with a single SHANNON_AI_MODEL across five providers * feat(cli): rebuild the setup wizard for provider and model selection * docs: document single-model selection and supported providers * feat(worker): use chat completions for OpenAI behind a custom base URL * feat: add SHANNON_AI_OPENAI_FORMAT to pick the wire API for OpenAI gateways * refactor(cli): drop endpoint path hints from the gateway format picker * feat(worker): enable pi in-session provider retry with retry-after backoff * refactor(worker): hand provider error classification to pi and drop the Anthropic ladders * refactor: remove the subscription retry preset and pipeline config section * fix(worker): validate Bedrock credentials with the same live probe as other providers * feat(worker): render the report from structured findings instead of agent-written markdown * fix(worker): dispose the credential probe session on every path * fix(worker): refuse to replace the assembled report with an empty one * refactor(worker): catch post-processing throws across the whole finalization block * revert(worker): drop the report zero-findings guard * docs(worker): correct the retry split and Bedrock credential claims * docs: regenerate llms-full.txt from current sources * feat(cli): build and run the npx flow from a clone * refactor(cli): flatten the setup summary output * feat(cli): reject runs with more than one provider configured * fix(worker): say a rejected bash call never ran * chore(cli): drop grok-4.3 and gpt-5.6-luna from the setup suggestions * feat(worker): capture structured finding locations for SARIF output * fix(worker): enumerate queue confidence so the report inherits it verbatim * feat(worker): give the reporting phase a mode-specific output schema * feat(worker): emit a SARIF 2.1.0 log for exploitative runs * fix(worker): correct SARIF locations and defer fingerprinting to the upload action * fix(worker): drop the confidence suffix from the analysis-mode summary list * feat(worker): give exploit findings a dedicated code location field * feat(worker): carry structured code locations from the vuln queue to the report * fix(worker): join code locations from the vuln queue instead of re-asking agents * fix(worker): spell out the finding_id to category mapping in the tool schema * feat: drop Google/Gemini as a supported AI provider * fix(worker): stop asking the report agent for code locations * docs: correct the provider list and drop the removed rate-limit settings * docs: add provider cyber safeguards and suggested models per provider * docs: document the SARIF output and the report rating thresholds
79 lines
2.9 KiB
TypeScript
79 lines
2.9 KiB
TypeScript
// Copyright (C) 2025 Keygraph, Inc.
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//
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// This program is free software: you can redistribute it and/or modify
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// it under the terms of the GNU Affero General Public License version 3
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// as published by the Free Software Foundation.
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/**
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* Attach vuln-queue code locations to collected findings.
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*
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* The vuln agent authors `code_locations` once, into its queue. Every stage after that used to
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* re-transcribe them — the exploit agent into its evidence, the report agent into `add_finding` —
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* and each hop lost some: 100% in the queue, 98% in the evidence, 42-63% by the report. Nothing
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* about the copy is a judgement call, and `finding_id` matches the queue `ID` exactly, so the
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* locations are joined here instead of being asked for again.
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*/
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import { fs, path } from 'zx';
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import type { QueueCodeLocation } from '../ai/queue-schemas.js';
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import type { AddFindingInput } from '../collectors/finding-collector.js';
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import type { ActivityLogger } from '../types/activity-logger.js';
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import { ALL_VULN_CLASSES } from '../types/config.js';
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interface QueueEntry {
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ID?: string;
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code_locations?: QueueCodeLocation[];
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}
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/** Read every per-class queue in the deliverables dir into an ID-to-locations map. */
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async function loadQueueLocations(
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deliverablesPath: string,
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logger: ActivityLogger,
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): Promise<Map<string, QueueCodeLocation[]>> {
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const locations = new Map<string, QueueCodeLocation[]>();
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for (const vulnClass of ALL_VULN_CLASSES) {
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const queuePath = path.join(deliverablesPath, `${vulnClass}_exploitation_queue.json`);
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if (!(await fs.pathExists(queuePath))) continue;
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try {
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const doc = (await fs.readJson(queuePath)) as { vulnerabilities?: QueueEntry[] };
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for (const entry of doc.vulnerabilities ?? []) {
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if (entry.ID && entry.code_locations && entry.code_locations.length > 0) {
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locations.set(entry.ID, entry.code_locations);
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}
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}
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} catch (error) {
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logger.warn(`Could not read ${vulnClass} queue for code locations: ${(error as Error).message}`);
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}
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}
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return locations;
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}
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/**
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* Return the findings with `code_locations` filled in from the queue.
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*
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* A finding with no matching queue entry keeps none — the join never invents one. Findings are
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* copied rather than mutated so the collector's own state stays untouched.
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*/
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export async function attachQueueCodeLocations(
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findings: readonly AddFindingInput[],
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deliverablesPath: string,
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logger: ActivityLogger,
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): Promise<AddFindingInput[]> {
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const byId = await loadQueueLocations(deliverablesPath, logger);
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if (byId.size === 0) return [...findings];
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let matched = 0;
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const joined = findings.map((finding) => {
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const locations = byId.get(finding.finding_id);
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if (!locations) return finding;
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matched += 1;
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return { ...finding, code_locations: locations };
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});
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logger.info(`Attached code locations to ${matched}/${findings.length} finding(s) from the vuln queues`);
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return joined;
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}
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