adversary

adversary is a skill for Claude Code, Codex from Tyox-all/Weave_Protocol. It costs 0 tokens per session (1,183 once invoked), scanned A, original, Apache-2.0.

An offensive testing tool for AI agents that generates documented and new attacks, then creates standardized scorecards.

In plain words
What is it for?
Use it to test prompt-injection and jailbreak resistance, check WARD.md policies, run safety regression checks, and prepare security or vendor-review scorecards.
Why use it?
It helps reveal whether an agent can be tricked, forced to misuse tools, or made to ignore its rules before release.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to test prompt-injection and jailbreak resistance, check WARD.md policies, run safety regression checks, and prepare security or vendor-review scorecards.

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Install with agentmods
npx agentmods add skills/tyox-all/weave_protocol/adversary
Install

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.

Any agent
npx skills add Tyox-all/Weave_Protocol --skill adversary
Clone the repo
git clone --depth 1 https://github.com/Tyox-all/Weave_Protocol

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for adversary

README.md
[![agentmods](https://agentmods.dev/badge/skills/tyox-all/weave_protocol/adversary/github.svg)](https://agentmods.dev/skills/tyox-all/weave_protocol/adversary)
Your own site
<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.

agentmods 80×15 button for adversary

Your own site · 80×15
<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>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,183 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured yesterday against content hash 50a44f5d330d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

The scan reads SKILL.md. This mod also ships 23 executable files (src/agent.ts, src/anthropic.ts, src/attacks/extraction/index.ts, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

adversary/SKILL.md · 118 lines

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 attack command for real-world testing

Read the full file on GitHub · 118 lines

Changes

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.

  1. yesterday Changed · +33 lines 50a44f5d330d
  2. 1mo ago First seen · 85 lines · 0 tokens per session scan A a4bc5a1bad5c

Subscribe to this mod's changes

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.