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 automateyournetwork/netclaw --skill ise-posture-auditgit clone --depth 1 https://github.com/automateyournetwork/netclawWrote 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/automateyournetwork/netclaw/ise-posture-audit)<a href="https://agentmods.dev/skills/automateyournetwork/netclaw/ise-posture-audit"><img src="https://agentmods.dev/badge/skills/automateyournetwork/netclaw/ise-posture-audit/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/automateyournetwork/netclaw/ise-posture-audit"><img src="https://agentmods.dev/badge/skills/automateyournetwork/netclaw/ise-posture-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Data Exfiltration · line 233 Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
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 | $0.00073 | $0.02605 |
| Opus 5 | $0.00036 | $0.01303 |
| Sonnet 5 | $0.00015 | $0.00521 |
| Haiku 4.5 | $0.00007 | $0.00261 |
Grade A, and why
ise-posture-audit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ISE Posture and Policy Audit
When to Use
- Periodic ISE policy compliance audit (SOC2, PCI-DSS, NIST 800-53, HIPAA)
- Pre-deployment review before onboarding new endpoint types
- Post-incident review to identify policy gaps that allowed lateral movement
- TrustSec segmentation validation
- Profiling accuracy assessment after network changes
- Quarterly access control hygiene check
How to Call the ISE MCP Tools
All ISE tools are called via mcp-call with the ISE MCP server command:
ISE_BASE=$ISE_BASE USERNAME=$ISE_USERNAME PASSWORD=$ISE_PASSWORD python3 $MCP_CALL "python3 -u $ISE_MCP_SCRIPT" TOOL_NAME '{"param":"value"}'
Audit Procedure
Step 1: Clear Cache and Establish Baseline
Start every audit with a fresh cache to ensure current data:
ISE_BASE=$ISE_BASE USERNAME=$ISE_USERNAME PASSWORD=$ISE_PASSWORD python3 $MCP_CALL "python3 -u $ISE_MCP_SCRIPT" clear_cache '{}'
Verify connectivity and cache state:
ISE_BASE=$ISE_BASE USERNAME=$ISE_USERNAME PASSWORD=$ISE_PASSWORD python3 $MCP_CALL "python3 -u $ISE_MCP_SCRIPT" get_cache_stats '{}'
Step 2: Authorization Policy Review
Pull all policy sets, then drill into authorization rules:
ISE_BASE=$ISE_BASE USERNAME=$ISE_USERNAME PASSWORD=$ISE_PASSWORD python3 $MCP_CALL "python3 -u $ISE_MCP_SCRIPT" network_access_policy_set '{}'
ISE_BASE=$ISE_BASE USERNAME=$ISE_USERNAME PASSWORD=$ISE_PASSWORD python3 $MCP_CALL "python3 -u $ISE_MCP_SCRIPT" network_access_authorization_rules '{}'
ISE_BASE=$ISE_BASE USERNAME=$ISE_USERNAME PASSWORD=$ISE_PASSWORD python3 $MCP_CALL "python3 -u $ISE_MCP_SCRIPT" network_access_authentication_rules '{}'
ISE_BASE=$ISE_BASE USERNAME=$ISE_USERNAME PASSWORD=$ISE_PASSWORD python3 $MCP_CALL "python3 -u $ISE_MCP_SCRIPT" network_access_conditions '{}'
Authorization Policy Checks:
| Check | What to Look For | Severity If Found |
|---|---|---|
| Default Allow | Default rule granting PermitAccess or DenyAccess without conditions | CRITICAL |
| Overly permissive rules | AuthZ rules with no posture condition and full network access | CRITICAL |
| Stale rules | Rules referencing deleted/unused identity groups or conditions | HIGH |
| Rule ordering | Permissive rules ranked above restrictive rules (shadowing) | HIGH |
| Missing posture check | AuthZ rules that grant access without posture assessment | MEDIUM |
| Duplicate conditions | Multiple rules with identical match criteria | LOW |
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.
- 9d ago First seen · 246 lines · 73 tokens per session scan A d2cdad054172
ise-posture-audit is a skill published in the GitHub repository automateyournetwork/netclaw (657 stars, last pushed 6d ago), licensed Apache-2.0. It adds 73 tokens to every session and 2,605 once invoked, about $0.0004 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 2026-09-03.
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