llm-security/tests/fixtures/posture-scan/grade-a-project/hooks/scripts/post-session-guard.mjs
Kjell Tore Guttormsen f153f969a0 feat(ultraplan-local): v1.6.0 — /ultraresearch-local deep research command
Add /ultraresearch-local for structured research combining local codebase
analysis with external knowledge via parallel agent swarms. Produces research
briefs with triangulation, confidence ratings, and source quality assessment.

New command: /ultraresearch-local with modes --quick, --local, --external, --fg.
New agents: research-orchestrator (opus), docs-researcher, community-researcher,
security-researcher, contrarian-researcher, gemini-bridge (all sonnet).
New template: research-brief-template.md.

Integration: --research flag in /ultraplan-local accepts pre-built research
briefs (up to 3), enriches the interview and exploration phases. Planning
orchestrator cross-references brief findings during synthesis.

Design principle: Context Engineering — right information to right agent at
right time. Research briefs are structured artifacts in the pipeline:
ultraresearch → brief → ultraplan --research → plan → ultraexecute.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-08 08:58:35 +02:00

40 lines
1.4 KiB
JavaScript

#!/usr/bin/env node
// post-session-guard.mjs — Runtime trifecta detection (Rule of Two)
// v5.0: Configurable TRIFECTA_MODE (block|warn|off), long-horizon 100-call window,
// behavioral drift via Jensen-Shannon divergence
import { readFileSync, appendFileSync } from 'node:fs';
const TRIFECTA_MODE = (process.env.LLM_SECURITY_TRIFECTA_MODE || 'warn').toLowerCase();
const SLIDING_WINDOW = 20;
const LONG_HORIZON_WINDOW = 100;
const input = JSON.parse(readFileSync('/dev/stdin', 'utf-8'));
const toolName = input.tool_name || '';
// Classify tool
function classifyTool(name) {
if (/Read|Glob|Grep/.test(name)) return 'read';
if (/Write|Edit/.test(name)) return 'write';
if (/Bash/.test(name)) return 'exec';
if (/WebFetch|WebSearch/.test(name)) return 'network';
return 'other';
}
// Jensen-Shannon divergence for behavioral drift detection
function jsDivergence(p, q) {
const m = p.map((pi, i) => (pi + q[i]) / 2);
let kl1 = 0, kl2 = 0;
for (let i = 0; i < p.length; i++) {
if (p[i] > 0 && m[i] > 0) kl1 += p[i] * Math.log2(p[i] / m[i]);
if (q[i] > 0 && m[i] > 0) kl2 += q[i] * Math.log2(q[i] / m[i]);
}
return (kl1 + kl2) / 2;
}
if (TRIFECTA_MODE === 'off') {
process.stdout.write(JSON.stringify({ decision: 'allow' }));
process.exit(0);
}
// Trifecta detection logic would go here (simplified for fixture)
process.stdout.write(JSON.stringify({ decision: 'allow' }));