SATAgent

Run the pure-LLM variant of the QLCoder workflow for both CVE samples and local Web App repositories. Supports multi-profile taint-flow analysis with source/...

QLCoder Pure LLM

Use this skill to drive pure-llm mode in the local QLCoder project with two workflows:

• CVE sample analysis from manifest (patch/advisory-driven).
• Local repository taint-flow typing for Web App codebases (Java Web, Python Web).

The local workflow now also emits a triaged security finding summary (taint_findings.analysis.*) focused on XSS / SQLi / broken-access-control classes.

Quick Start

1. Confirm the workspace contains qlcoder/cli.py.
2. Prefer the helper script: python /Users/aibot/.codex/skills/coder-pure-llm/scripts/run_pure_llm.py --workspace /path/to/workspace
3. For CVE mode, optionally pass --project-slug <slug> or --batch-limit N.
4. For local Web App mode, pass: --repo-path /path/to/repo --app-profile auto
5. Read generated artifacts under runs/.../pure-llm/.

Workflow

A. CVE Manifest Mode

1. Reuse an existing manifest under datasets/manifests/ when possible.
2. If missing, build base manifest: python -m qlcoder.cli build-manifest --base-only --allow-manual-override --manual-base-ref master
3. Run single sample (run-one-pure-llm) or batch (run-manifest-pure-llm).
4. Summarize:
   • summary
   • source_hypotheses
   • sink_hypotheses
   • sanitizer_hypotheses
   • draft_query_strategy
   • draft_query_text

B. Local Web App Mode (Java/Python)

1. Run: python /Users/aibot/.codex/skills/coder-pure-llm/scripts/run_pure_llm.py --workspace /path/to/workspace --repo-path /path/to/repo --app-profile auto
2. --app-profile values:
   • auto: detect by repository file distribution; mixed repositories can run both Java and Python profiles.
   • java-web: force Java Web source/sink/sanitizer typing.
   • python-web: force Python Web source/sink/sanitizer typing.
3. First review taint_findings.analysis.json/md for prioritized findings and severity.
4. Then use taint_profile.analysis.json/md for deeper source/sink/sanitizer trace evidence.
5. Treat these results as taint-flow leads for manual trace confirmation.

Source/Sink Type Reference

See references/taint_profiles.md for the taxonomy used by the local Web App profile report.

Output Contract

CVE manifest mode artifacts

• runs/<project_slug>/pure-llm/iteration_00.prompt.md
• runs/<project_slug>/pure-llm/iteration_00.analysis.json
• runs/<project_slug>/pure-llm/iteration_00.analysis.md
• runs/<project_slug>/pure-llm/iteration_01.analysis.json
• runs/<project_slug>/pure-llm-summary.json

Local Web App mode artifacts

• runs/local-<analysis_name_or_repo>/pure-llm/analysis.json
• runs/local-<analysis_name_or_repo>/pure-llm/analysis.md
• runs/local-<analysis_name_or_repo>/pure-llm/taint_profile.analysis.json
• runs/local-<analysis_name_or_repo>/pure-llm/taint_profile.analysis.md
• runs/local-<analysis_name_or_repo>/pure-llm/taint_findings.analysis.json
• runs/local-<analysis_name_or_repo>/pure-llm/taint_findings.analysis.md

Treat JSON artifacts as source of truth. Use Markdown for human-readable review.

Notes

• Do not claim CodeQL validation in this mode.
• Missing patch or advisory files are tolerated; the workflow should still proceed using whatever metadata is available.
• Taint profile output is pattern-based candidate analysis, not full dataflow proof.
• Java ${...} sink typing is de-noised to mapper SQL context to avoid common pom.xml/config placeholder false positives.
• The findings summary is heuristic triage; always verify exploitability with targeted trace/tests.
• For detailed command patterns and wrapper usage, read references/workflow.md.