Borrowing it
Nothing to install: this file belongs to SCStelz/security-investigator. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SCStelz/security-investigator/main/.github/skills/ca-policy-investigation/SKILL.mdgit clone --depth 1 https://github.com/SCStelz/security-investigatorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/scstelz/security-investigator/ca-policy-investigation)<a href="https://agentmods.dev/skills/scstelz/security-investigator/ca-policy-investigation"><img src="https://agentmods.dev/badge/skills/scstelz/security-investigator/ca-policy-investigation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/scstelz/security-investigator/ca-policy-investigation"><img src="https://agentmods.dev/badge/skills/scstelz/security-investigator/ca-policy-investigation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 240 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00104 | $0.03368 |
| Opus 5 | $0.00052 | $0.01684 |
| Sonnet 5 | $0.00021 | $0.00674 |
| Haiku 4.5 | $0.00010 | $0.00337 |
Grade A, and why
ca-policy-investigation 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 383 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Conditional Access Policy Investigation - Instructions
Purpose
This skill investigates Conditional Access (CA) policy changes in correlation with sign-in failures to detect:
- Legitimate troubleshooting (authorized policy changes to resolve access issues)
- Security control bypass (unauthorized policy modifications to circumvent blocks)
- Privilege abuse (users with admin rights weakening security controls)
The key distinction is whether policy changes were authorized and necessary vs self-service bypass of security controls.
📑 TABLE OF CONTENTS
- Critical Investigation Rules - Mandatory workflow steps
- Common Error Codes - Sign-in failure reference
- CA Policy States - Understanding policy modes
- 5-Step Investigation Workflow - KQL queries and analysis
- Real-World Example - Complete walkthrough
- Critical Mistakes - What NOT to do
- Security Recommendations - Remediation guidance
Critical Investigation Rules
When investigating sign-in failures (error codes 53000, 50074) with CA policy correlation:
⚠️ MANDATORY STEPS - DO NOT SKIP:
- Query ALL CA policy changes in chronological order (±2 days from failure time)
- Parse policy state transitions from the JSON (enabled → disabled → report-only)
- Compare failure timeline with policy change timeline
- Verify logical consistency: Ask "does this make sense?"
Key Questions to Answer:
- Was the user blocked BEFORE the policy change?
- Did the policy change resolve the block?
- Who initiated the policy change? (same user = suspicious)
- What was the business justification?
Common Error Codes
| Error Code | Description | Typical Cause |
|---|---|---|
| 53000 | Device not compliant | Device not enrolled in Intune or failing compliance checks |
| 50074 | Strong authentication required | MFA not satisfied |
| 50074 | User must enroll in MFA | MFA not configured for user |
| 530032 | Blocked by CA policy | Generic CA policy block |
| 65001 | User consent required | Application consent needed |
| 53003 | Access blocked by CA policy | Explicit block condition met |
| 70044 | Session expired | User needs to re-authenticate |
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.
- 13d ago First seen · 383 lines · 104 tokens per session scan A d3b7fb7ce88f
ca-policy-investigation is a skill published in the GitHub repository SCStelz/security-investigator (245 stars, last pushed 4d ago), licensed MIT. It adds 104 tokens to every session and 3,368 once invoked, about $0.0005 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.
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