define-security-policy
Skill2 starsChanged 47 days agoMITView on GitHub
Creates or updates SECURITY.md and authorization scope for a repo in the Defense Factory prepare phase. Use when starting a defensive assessment, before inventory or scans, or when SLA/ownership rules are missing.
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 2 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 15
Before build-inventory or any scan/validation skill
- Distinctive: line 20
Write access to the target repository (or a docs location they specify).
- Very specific: line 21
Prefer running python scripts/init_workspace.py --root <repo> first so .defense-factory/ exists.
- Very specific: line 32
Write or update SECURITY.md at repo root with sections:
- Distinctive: line 54
Do not invent legal authorization.
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
define-security-policy
Phase: Prepare / shared context
Style: Blue (defensive)
When to use
- Project has no usable
SECURITY.md - Scope, authorization, or severity SLAs are unclear
- Before
build-inventoryor any scan/validation skill
Preconditions
- User intends authorized defensive work on an owned or authorized system.
- Write access to the target repository (or a docs location they specify).
- Prefer running
python scripts/init_workspace.py --root <repo>first so.defense-factory/exists.
Procedure
- Locate existing policy: repo-root
SECURITY.md, then.defense-factory/SECURITY.md. - Interview or infer from repo docs:
- Owner / security contact
- In-scope assets and environments
- Explicit out-of-scope items
- Written authorization boundaries for any dynamic testing
- Severity → SLA mapping
- Write or update
SECURITY.mdat repo root with sections:- Authorization
- Scope (in / out)
- Severity and SLA
- Ownership defaults and escalation
- Validation rules (dynamic evidence required)
- Remediation rules (merge ≠ verified)
- Reporting contact
- Mirror a pointer or copy under
.defense-factory/SECURITY.mdviainit_workspace.pyif the workspace is new. - Record a short changelog note in
.defense-factory/inventory/_policy_init.mdwith date and author.
Required outputs
| Path | Content |
SECURITY.md | Authoritative policy |
.defense-factory/SECURITY.md | Stub or pointer |
.defense-factory/inventory/_policy_init.md | Init note |
Stop / refuse
- Refuse to encode authorization for attacking third-party systems the user does not own or lack written permission to test.
- Do not invent legal authorization; require the user to state ownership or provide an authorization reference.
Next phase
Proceed to threat-model, then build-inventory.
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- openai/codex-security★ 11ksame name
- openai/plugins★ 7.4ksame name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository10 other files it gives its agents.
- AGENTS.mdAGENTS.md
- build-inventorySkill
- dedupe-findingsSkill
- fix-findingSkill
- route-ownershipSkill
- security-diff-scanSkill
- security-scanSkill
- threat-modelSkill
- triage-validate-findingSkill
- verify-fixSkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

