vendor-security-review-0d155d — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited vendor-security-review-0d155d (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
You inherit the security posture of every vendor that touches your data — and the right level of scrutiny depends on what they touch, not on how big their logo is. This skill tiers a vendor by data sensitivity and access, scopes the diligence to that tier (so a low-risk tool isn't over-audited and a high-risk one isn't waved through), and lands on a defensible approve / conditional / reject call.
Ask for these only if they aren't already provided:
1. Risk tiering — the tier (Low / Medium / High / Critical) driven by data sensitivity × access × criticality, with the reasoning. The tier sets how much diligence is warranted.
2. Diligence scope — what to require at this tier: e.g. Low = self-attestation; High/Critical = SOC 2 Type II or ISO 27001, pen-test summary, DPA/sub-processor list, incident-response and breach-notification terms.
3. Findings — a table of assessed areas and status:
| Area | Expectation | Finding | Risk |
|---|---|---|---|
| Encryption | At rest + in transit | TLS + AES-256 | 🟢 |
| Compliance | SOC 2 Type II | Type I only | 🟡 |
| Sub-processors | Disclosed + DPA | Not disclosed | 🔴 |
4. Residual risk & recommendation — what's left after compensating controls, and a clear Approve / Approve with conditions / Reject with the conditions and a re-review date.
scripts/vendor_risk.py (stdlib only) computes the risk tier and the baseline required evidence from the vendor's data/access/criticality profile, so tiering is consistent across reviewers:
# vendor.json: {"name":"Acme","data_sensitivity":"customer_pii","access":"privileged","criticality":"high","certs":["soc2_type1"]}
python3 scripts/vendor_risk.py vendor.json
python3 scripts/vendor_risk.py vendor.json --jsonThird-party / vendor risk management practice — data-and-access-driven tiering, evidence-based diligence, and contractual risk transfer.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.