BLA
BLA (Blind LLM Agents) is the open-source Blue Defense MCP and CLI built to protect software artifacts against automated AI reverse-engineering workflows.
翻译准备中
OpenAI 的 Codex Security CLI 和 TypeScript SDK,用于发现、验证和修复安全漏洞。npm: https://www.npmjs.com/package/@openai/codex-security
AI 翻译
OpenAI's Codex Security CLI and TypeScript SDK for finding, validating, and fixing security vulnerabilities. npm: https://www.npmjs.com/package/@openai/codex-security
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@openai/codex-security is a CLI and TypeScript SDK for defining security policy and finding, validating, and fixing security vulnerabilities in your code.
👉👉 See the Codex Security documentation for full documentation.
Some cybersecurity requests and protected findings require approval through
Trusted Access for Cyber. To join the program, visit
chatgpt.com/cyber.
Requires Node.js 22.13.0 or later and Python 3.10 or later.
For CI, set OPENAI_API_KEY instead of signing in.
Draft repository-wide or component-scoped SECURITY.md guidance for future scans:查看完整 README ↗Codex Security helps you find, investigate, and fix vulnerabilities in your code.
Use its security workflows in Codex, or automate them with the
@openai/codex-security CLI and TypeScript SDK.
SECURITY.md policies and save threat models for later review.Open your repository in a Codex session with the Codex Security plugin enabled, then ask:
Run a Codex Security scan on this repository, focusing on authentication and authorization. Return the saved report, source evidence, and coverage limits.
A completed scan saves a report, findings, coverage, and a threat model when available. Use those results to investigate findings, request a patch, or verify an existing fix. See the agent workflow guide for plugin setup, task selection, and recovery when required tools are unavailable.
Requires Node.js 22.13.0+ within 22.x, or Node.js 24.x or 26.x, and Python 3.10+.
Python 3.10 also requires tomli.
Install the CLI globally and sign in:
npm install --global @openai/codex-security
cs login
cs is a short alias for codex-security; both commands run the same CLI.
The installation creates both commands in npm's global executable directory,
which must be on your PATH. If cs already resolves to another tool, use
codex-security instead. If npm stops with an EEXIST error for cs, use
npx @openai/codex-security without a global installation.
Run your scan from the repository directory:
cs scan .
If you have Daybreak Blue access, add --cyber-access-program daybreak_blue
to the scan command. Otherwise, omit the flag or use
--cyber-access-program standard.
To use Codex's Daybreak toggle, pass --codex daybreak=true. It defaults off
and requires compatible access. See Daybreak configuration
for SDK and plugin usage, including Deep Scan workers.
Scans use your existing SECURITY.md guidance. You can optionally
draft or update a policy before scanning.
To run without a global installation, replace cs in these examples with
npx @openai/codex-security, for example:
npx @openai/codex-security scan .
For CI, set OPENAI_API_KEY or CODEX_API_KEY in the scan process's environment.
On remote or headless machines, use login --device-auth if your workspace
allows it, or sign in over SSH.
Some cybersecurity requests and protected findings require Trusted Access for Cyber approval.
Choose a scope and scan mode:
# Scan selected paths.
cs scan . --path src --path tests
# Scan committed changes from a base revision to HEAD.
cs scan . --diff origin/main
# Run a deep scan of the repository.
cs scan . --mode deep
Use cs scan . --max-time 15 for an advisory 15-minute Standard investigation
allowance. See investigation time
for timing semantics and Deep Scan limits.
Use cs --help to browse commands, or cs scan --help
for scan options, cost limits, and patching after a scan.
For an application spread across repositories, see review one system across repositories. Use bulk scans for independent repository reviews in one resumable campaign.
After a scan, inspect its scope and follow-up work to understand recorded exclusions and decide whether to review the findings, run a focused scan, or recover an interrupted run.
Install the package locally in your TypeScript project:
npm install @openai/codex-security
Then import it:
import { CodexSecurity } from "@openai/codex-security";
const security = new CodexSecurity();
try {
const result = await security.run("/path/to/repository");
console.log(result.reportPath);
} finally {
await security.close();
}
The SDK guide includes deep-scan configuration, validation, severity classification, owner suggestions, and result handling.
When Codex Security Cloud is available to your account, the Security plugin's
$cloud-findings skill can read findings, reports, recorded assignment and
verification, and scan status in Codex desktop or the Codex CLI. Cloud is an
optional connection; local scans work without it.
See Cloud connection setup and CLI reads for authentication requirements and a read-only example.
Use policy to draft a new SECURITY.md or update an existing one. Use --path
to select a component:
cs policy .
cs policy . --path services/api --knowledge-base architecture.md
The command saves its draft outside the repository and leaves existing files
unchanged. Review the diff and notes, edit the draft, then copy only SECURITY.md
to the displayed Policy target. Keep the saved architecture and threat-model
documents outside the repository.
Scans already use root and component SECURITY.md files. Keep your current policy
if it needs no changes. When updating it, preserve its vulnerability-reporting
instructions. If the command says the policy is already up to date, no copy is
needed.
Files at .github/SECURITY.md or docs/SECURITY.md often contain reporting
instructions. Preserve them when drafting a policy; those locations do not
automatically provide repository-wide scan guidance. See the
policy guide for policy
locations, unanswered questions, saved artifacts, and SDK usage.
Scans and policy generation save threat models with their results. Export a saved model without starting another analysis:
cs export --scan SCAN_ID --artifact threat-model --output threatmodel.md
Omit --scan to use the current repository's latest completed scan. The
export guide also covers findings,
SARIF output for CI, and the offline TypeScript API. For ServiceNow Application
Vulnerability Response, see Export findings for ServiceNow.
Run scheduled, manual, or pull request scans with the GitHub Action. For a weekly
repository scan, add an OpenAI API key as the repository secret
CODEX_SECURITY_API_KEY, then save this workflow in
.github/workflows/codex-security.yml. Replace REPLACE_WITH_REVIEWED_COMMIT
with the full SHA of an Action commit.
This workflow requests Daybreak Blue. Use an API key from a project with Blue
enabled; without Daybreak access, omit cyber-access-program or set it to
standard.
name: Codex Security
on:
workflow_dispatch:
schedule:
- cron: "23 7 * * 1" # Mondays at 07:23 UTC
permissions:
contents: read
jobs:
security:
runs-on: ubuntu-24.04
steps:
# Configure Bubblewrap and AppArmor so Codex Security can run safely in its sandbox.
- name: Set up the Ubuntu sandbox
run: |
sudo apt-get update
sudo apt-get install --yes bubblewrap apparmor-profiles
sudo apparmor_parser -r /usr/share/apparmor/extra-profiles/bwrap-userns-restrict
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
with:
persist-credentials: false
- uses: openai/codex-security@REPLACE_WITH_REVIEWED_COMMIT
with:
model: gpt-5.6-sol
effort: high
cyber-access-program: daybreak_blue
env:
OPENAI_API_KEY: ${{ secrets.CODEX_SECURITY_API_KEY }}
Findings are report-only by default. Set a severity threshold to fail on reported findings at or above it. Scanner and required reporting errors fail the job; intentional file exclusions and investigation notes do not. See the Action setup and input reference for PR scans, severity thresholds, and report uploads.
Scan a list of repositories with the included Docker Compose configuration, which keeps results and authentication between runs. See the container quick start. The workflow runner runs individual CLI stages in containers and can connect to a separately deployed findings service.
The findings guide covers local
storage, deduplication, and compatibility with independently operated endpoints
through publish scan --to custom and explicit --findings-url. The local
serve command and browser dashboard have been removed; existing databases and
scan artifacts remain available.
Scans support OpenAI, Amazon Bedrock, OpenRouter, Fireworks AI, and Cheaper Inference. Bedrock uses AWS credentials and does not require a separate OpenAI login. See Bedrock setup for AWS profiles, regions, and model access.
For OpenRouter, Fireworks AI, and Cheaper Inference, set the provider's API key and choose a supported model. See provider configuration for examples.
To report a vulnerability privately, follow the security policy.