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.
npx skills add VincentChuWaiChow/vanguard-frontier-agentic --skill alibaba-ram-iam-reviewgit clone --depth 1 https://github.com/VincentChuWaiChow/vanguard-frontier-agenticWrote 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/vincentchuwaichow/vanguard-frontier-agentic/alibaba-ram-iam-review)<a href="https://agentmods.dev/skills/vincentchuwaichow/vanguard-frontier-agentic/alibaba-ram-iam-review"><img src="https://agentmods.dev/badge/skills/vincentchuwaichow/vanguard-frontier-agentic/alibaba-ram-iam-review/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/vincentchuwaichow/vanguard-frontier-agentic/alibaba-ram-iam-review"><img src="https://agentmods.dev/badge/skills/vincentchuwaichow/vanguard-frontier-agentic/alibaba-ram-iam-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00049 | $0.00898 |
| Opus 5 | $0.00024 | $0.00449 |
| Sonnet 5 | $0.00010 | $0.00180 |
| Haiku 4.5 | $0.00005 | $0.00090 |
Grade A, and why
alibaba-ram-iam-review 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 12d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alibaba Cloud RAM IAM Review
Purpose
Act as the RAM IAM reviewer who assumes every AdministratorAccess assignment, missing MFA binding, and overly broad Control Policy gap is a privilege escalation risk until proven otherwise.
When to use
Use this skill for:
- RAM user inventory: active users, MFA status, AccessKey rotation age, console vs. API-only access
- RAM group and policy review: group membership, attached policies, inline vs. managed policy assessment
- RAM role review: role trust policies, attached permissions, cross-account trust configurations, and impersonation chain analysis
- STS (Security Token Service) token lifecycle: token validity period, scope, and application-level credential caching
- Resource Directory assessment: org tree structure, Control Policy (SCP equivalent) coverage, and member account permission boundaries
- Privilege escalation path analysis: roles that can assume other roles, policies that grant iam:* permissions, and AdministratorAccess bindings
- AccessKey lifecycle: keys older than 90 days with no rotation are stale risk; keys assigned to inactive users are critical findings
Key Alibaba Cloud specifics
- RAM AdministratorAccess on any user, group, or role is a critical finding — it grants full control over all Alibaba Cloud resources in the account, equivalent to account root.
- Resource Directory creates an org tree. Control Policy (equivalent to AWS SCPs) overrides RAM policies in member accounts — a Control Policy that denies an action blocks it even if RAM explicitly allows it. Test Control Policy changes in simulation before enforcement.
- STS tokens have a maximum validity of 1 hour (3600 seconds) for standard tokens; 12 hours for long-term tokens on specific service roles. Applications that cache STS tokens must handle token expiry gracefully.
- RAM role trust policies define which principals (users, services, or accounts) can call
sts:AssumeRoleon that role. A misconfigured trust policy (wildcard principal or missing condition) enables privilege escalation by unauthorized callers. - AccessKey rotation: keys with last-used date > 90 days ago and no rotation are stale. Keys assigned to users who no longer exist or have been disabled are critical security gaps.
- RAM users should use MFA for console access. API-only users should use AccessKeys with minimum required permissions — no console access needed.
- The
sts:AssumeRolepermission on a role effectively grants all that role's permissions to the caller — treat it as a privilege amplification vector.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 67 lines · 49 tokens per session scan A 9052f9f0d966
alibaba-ram-iam-review is a skill published in the GitHub repository VincentChuWaiChow/vanguard-frontier-agentic (22 stars, last pushed today), licensed Apache-2.0. It adds 49 tokens to every session and 898 once invoked, about $0.0002 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.
Other skills, from other repositories
auditing-azure-active-directory-configuration
Auditing Microsoft Entra ID (Azure Active Directory) configuration to identify risky authentication policies, overly permissive role assignments, stale accounts, conditional access gaps, and guest user risks using AzureAD PowerShell, Microsoft Graph API, and ScoutSuite.
analyzing-azure-activity-logs-for-threats
Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query to detect suspicious administrative operations, impossible travel, privilege escalation, and resource modifications. Builds KQL queries for threat hunting in Azure environments. Use when investigating suspicious Azure tenant activity or…
implementing-azure-defender-for-cloud
Implementing Microsoft Defender for Cloud to enable cloud security posture management, workload protection across VMs, containers, databases, and storage, configure security recommendations, and set up adaptive security controls with automated remediation.
detecting-misconfigured-azure-storage
Detecting misconfigured Azure Storage accounts including publicly accessible blob containers, missing encryption settings, overly permissive SAS tokens, disabled logging, and network access violations using Azure CLI, PowerShell, and Microsoft Defender for Storage.
detecting-azure-lateral-movement
Detect lateral movement in Azure AD/Entra ID environments using Microsoft Graph API audit logs, Azure Sentinel KQL hunting queries, and sign-in anomaly correlation to identify privilege escalation, token theft, and cross-tenant pivoting.
subdomain-takeover-hunt
Detect and verify subdomain takeover via dangling CNAME to unclaimed services.