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 yogsoth-ai/stress-test --skill structured-attack-campaigngit clone --depth 1 https://github.com/yogsoth-ai/stress-testWrote 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/yogsoth-ai/stress-test/structured-attack-campaign)<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/structured-attack-campaign"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/structured-attack-campaign/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/yogsoth-ai/stress-test/structured-attack-campaign"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/structured-attack-campaign.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00031 | $0.00535 |
| Opus 5.5 | $0.00012 | $0.00214 |
| Sonnet 5.5 | $0.00006 | $0.00107 |
| Haiku 4.5 | $0.00003 | $0.00053 |
Grade A, and why
structured-attack-campaign 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 1mo 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Structured Attack Campaign Tactic
Complete attack lifecycle from surface enumeration through probing to aggregated findings.
Orchestration
- threat-surface-mapping enumerates all attackable surfaces of the artifact
- attack-vector-generation produces prioritized attack vectors per surface
- probe-execution executes each vector, records outcome (success/failure/partial)
- Partial successes trigger follow-up vector generation (depth-first on promising attacks)
- finding-aggregation deduplicates, classifies, and ranks all findings
- attack-resilience-scoring computes coverage metrics and overall resilience score
Subagents Dispatched
- threat-surface-mapping (1 call at start)
- attack-vector-generation (1 call per surface)
- probe-execution (1 call per vector, budget-limited)
- finding-aggregation (1 call at end)
- attack-resilience-scoring (1 call at end)
Termination Conditions
- All budgeted attack vectors exhausted
- All surfaces probed to at least depth 1
- Critical vulnerability found (early termination with immediate report)
- Diminishing returns: 3 consecutive probes yield no new findings
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| attack-resilience-scoring | Compute overall resilience score (0.0-1.0) based on attack results, coverage, and vulnerability severity distribution. |
| attack-vector-generation | Generate specific attack strategies for a given threat surface, producing concrete probes that can be executed. |
| finding-aggregation | Aggregate, deduplicate, and classify findings from multiple probes into a coherent vulnerability report. |
| probe-execution | Execute a single attack probe against an artifact, record the result with evidence and severity classification. |
| threat-surface-mapping | Enumerate all attackable surfaces of an artifact — logical, empirical, methodological, social, and practical dimensions. |
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.
- 1mo ago First seen · 63 lines · 31 tokens per session scan A d4670a17055c
structured-attack-campaign is a skill published in the GitHub repository yogsoth-ai/stress-test (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 31 tokens to every session and 535 once invoked, about $0.0001 per session on Opus 5.5. 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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