vulnerability-db AGENTS.md

Project instructions for AppThreat Vulnerability Database, an offline database of known software vulnerabilities used by scanners.

In plain words
What is it for?
Use them when modifying vulnerability sources, package and version matching, offline SQLite lookups, database builds, or resource limits.
Why use it?
They explain the project's priorities and structure so agents do not mistake intentional design choices for bugs or make unsafe changes to security data.

Instructions file for CodexOpenCode

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/appthreat/vulnerability-db/agents-md
Clone the repo
git clone --depth 1 https://github.com/AppThreat/vulnerability-db

Made for: Codex, OpenCode.

Per session 2,646 This file is loaded in full into every session.
When invoked 2,646 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.02646 $0.02646
Opus 5 $0.01323 $0.01323
Sonnet 5 $0.00529 $0.00529
Haiku 4.5 $0.00265 $0.00265

Measured 2d ago against content hash ff56c2cbb438, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

vulnerability-db AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 252 lines

How it starts

The opening of the file, as written. The whole thing — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Guidance for AI coding agents and automated contributors working on appthreat-vulnerability-db.

If you are using VDB rather than changing it, read SKILL.md instead. This file is about working on the code.

What this project is

vdb builds and queries an offline SQLite vulnerability database from AppThreat vuln-list, OSV, NVD, GitHub and npm. It is used as a CLI and as a Python library by downstream scanners.

Four goals, in the order they win arguments:

Accurate package locator and version matching. A wrong answer here becomes a wrong security decision downstream, so accuracy beats size and speed.

Fast offline lookup from pre-built .vdb7 files, with no network access during a scan.

Reproducible builds. App-only and app+OS databases, plus per-type shards, from a fresh build every time. There is no migration path and none is wanted.

Bounded resource use on large feeds. Memory and disk are first-class constraints, not afterthoughts.

Repository map

vdb/cli.py              CLI entry point, cache/download/search orchestration
vdb/lib/config.py       environment-driven source, path and database config
vdb/lib/db.py           SQLite connections, schema, pragmas, finalization
vdb/lib/shard_store.py  shard store discovery, fan-out, coverage, staleness
vdb/lib/shard_split.py  the splitter: full database to per-type shards
vdb/lib/db_cmd.py       the `vdb db` subcommand
vdb/lib/cve.py          CVE 5.2 conversion and storage
vdb/lib/osv.py          OSV feed ingestion and conversion
vdb/lib/aqua.py         AppThreat/Aqua vuln-list ingestion, incl. OS distros
vdb/lib/gha.py          GitHub advisory ingestion
vdb/lib/nvd.py          NVD ingestion and the shared CVE-5 conversion
vdb/lib/cpe.py          CPE parsing, normalisation, separator variants
vdb/lib/vers.py         the single version comparison implementation
vdb/lib/search.py       query APIs and result materialization
vdb/lib/search_index.py metadata indexes for text/alias/reference/symbol
test/                   pytest suite and small fixture data
contrib/                measurement harnesses and their findings documents
docs/                   reference docs: DATABASE.md (schema + queries), DESIGN.md (shard client architecture), BENCHMARKS.md
packages/mcp-server-vdb/ MCP server, depends on the library API

Read the full file on GitHub · 252 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 252 lines · 2,646 tokens per session scan A ff56c2cbb438

Subscribe to this mod's changes

vulnerability-db AGENTS.md is an instructions file published in the GitHub repository AppThreat/vulnerability-db (148 stars, last pushed 3d ago), licensed MIT. It adds 2,646 tokens to every session, about $0.0132 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.