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 Tyox-all/Weave_Protocol --skill adversarygit clone --depth 1 https://github.com/Tyox-all/Weave_ProtocolWrote 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/tyox-all/weave_protocol/adversary)<a href="https://agentmods.dev/skills/tyox-all/weave_protocol/adversary"><img src="https://agentmods.dev/badge/skills/tyox-all/weave_protocol/adversary/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/tyox-all/weave_protocol/adversary"><img src="https://agentmods.dev/badge/skills/tyox-all/weave_protocol/adversary.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 | $0.00000 | $0.01183 |
| Opus 5.5 | $0.00000 | $0.00473 |
| Sonnet 5.5 | $0.00000 | $0.00237 |
| Haiku 4.5 | $0.00000 | $0.00118 |
Grade A, and why
adversary 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 yesterday.
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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
⚔️ Adversary skill — offensive testing for AI agents
You have access to @weave_protocol/adversary v0.3 — a package that generates 68 documented and novel attacks against AI agents and produces standardized scorecards. v0.3 adds LLM-driven dynamic mutation: when a target half-blocks an attack, an LLM synthesizes a variant and Adversary retries.
Dynamic mode (v0.3)
Adversary can now retry variants when the target half-blocks — refuses to comply but engages with the topic (e.g., "I can't help with that, but here's some general info about..."). An LLM synthesizes a novel variant of the payload and Adversary retries with it. Up to --dynamic-max-retries=<n> variants per attack (default 2).
Enable with --dynamic. Requires ANTHROPIC_API_KEY. Cost: ~$0.03 on top of a --real run (Haiku).
# Dynamic mode against real Claude
weave-adversary demo --real --dynamic
# Against a real agent endpoint
weave-adversary attack --url=https://my-agent.com/run --dynamic
The 68-attack corpus is unchanged — dynamic mode is a RETRY mechanism, not a corpus replacement. If the first attempt fully lands (breach) or fully blocks (hard refusal), no LLM call is made.
Programmatic:
import { AdversarialAgent, DemoTarget, DynamicAttackMutator } from '@weave_protocol/adversary';
const target = new DemoTarget({ mode: 'real' });
const mutator = new DynamicAttackMutator({ maxRetries: 2 });
const agent = new AdversarialAgent(target, { mutator });
const scorecard = await agent.run({ dynamic: true });
// scorecard.dynamic — mutation metadata + cost
// scorecard.findings[i].attempts — per-attempt payload/response/engagement
Scorecard schema v1.0 is preserved. AgentSecBench compat unchanged.
When to invoke
Use Adversary when the user:
- Wants to test an AI agent's security posture
- Is reviewing/auditing a WARD.md policy and wants to verify it holds
- Is preparing for a release and wants a regression check on safety
- Asks about agent red-teaming, prompt injection testing, or jailbreak resistance
- Wants to generate a scorecard for compliance / vendor review
- Has a real running agent (HTTP endpoint, CLI executable, or browser-driving code) — use the
attackcommand for real-world testing
What ships with it
28 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.
- .gitignore 36 B
- package-lock.json 3.2 KB
- package.json 1.7 KB
- README.md 11 KB
- src/agent.ts 8.3 KB runs code
- src/anthropic.ts 4.3 KB runs code
- src/attacks/extraction/index.ts 3.7 KB runs code
- src/attacks/goal_corruption/index.ts 4.4 KB runs code
- src/attacks/index.ts 1.8 KB runs code
- src/attacks/ipi/index.ts 21 KB runs code
- src/attacks/jailbreak/index.ts 8.2 KB runs code
- src/attacks/tool_coercion/index.ts 8.6 KB runs code
- src/cli.ts 22 KB runs code
- src/dynamic.ts 6.0 KB runs code
- src/index.ts 1.4 KB runs code
- src/scorecard/index.ts 232 B runs code
- src/scorecard/json.ts 339 B runs code
- src/scorecard/markdown.ts 5.2 KB runs code
- src/scorecard/redact.ts 1.2 KB runs code
- src/scorecard/scoring.ts 2.9 KB runs code
- src/targets/browser.ts 3.0 KB runs code
- src/targets/demo.ts 14 KB runs code
- src/targets/index.ts 195 B runs code
- src/targets/playwright.ts 17 KB runs code
- src/types.ts 7.8 KB runs code
- src/ward.ts 5.2 KB runs code
- test/dynamic.test.mjs 4.8 KB runs code
- tsconfig.json 508 B
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.
- yesterday Changed · +33 lines 50a44f5d330d
- 1mo ago First seen · 85 lines · 0 tokens per session scan A a4bc5a1bad5c
adversary is a skill published in the GitHub repository Tyox-all/Weave_Protocol (0 stars, last pushed 2d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,183 tokens. 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 2026-08-31.
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