agentsecbench

A security benchmark for AI agents that runs fixed, versioned attack tests and produces reports with graded tiers.

In plain words
What is it for?
Use it to run standard suites, save reports, measure the effect of WARD.md, compare results, and prepare material for reviews or audits.
Why use it?
It provides repeatable results for comparing agents or checking whether a new version or policy has reduced security.

Skill for Claude CodeCodex

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.

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

Made for: Claude Code, Codex.

Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 622 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.00622
Opus 5 $0.00000 $0.00311
Sonnet 5 $0.00000 $0.00124
Haiku 4.5 $0.00000 $0.00062

Measured 2d ago against content hash ecab3ad567de, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agentsecbench 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 2d ago.

The scan reads SKILL.md. This mod also ships 12 executable files (src/cli.ts, src/compare/index.ts, src/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.

agentsecbench/SKILL.md · 70 lines

How it starts

The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.

🎯 AgentSecBench skill — standardized agent security benchmarking

You have access to @weave_protocol/agentsecbench — a benchmark package that runs locked, versioned attack suites against AI agents and produces tier-graded reports.

When to invoke

Use AgentSecBench when the user:

  • Wants a citable score for an agent ("Tier B, 87/100 on ASB-Browser-v1")
  • Asks to compare two agents or two versions of the same agent
  • Needs a paste-ready security review artifact for a blog, RFP, or audit
  • Asks whether their WARD policy actually does anything
  • Wants to detect a regression between runs (e.g. in CI)

For raw attack execution without the interpretation layer, use @weave_protocol/adversary directly instead.

Key commands

# Run the canonical browser suite
agentsecbench run --suite=ASB-Browser-v1

# Save report
agentsecbench run --json=./report.json --md=./report.md

# Measure WARD contribution (runs twice)
agentsecbench run --measure-ward-delta

# Compare two reports
agentsecbench compare baseline.json new.json

# Show suite info / list suites
agentsecbench suite ASB-Browser-v1
agentsecbench suite  # lists all

What's in a Report

  • Tier (A/B/C/D/F) — headline grade
  • Score (0-100) — raw Adversary score
  • Category gaps — which attack classes failed
  • Trophy performance — pass/fail against 4 named real-world attacks (Atlan, EchoLeak, Brave/Comet, Forcepoint)
  • WARD delta (optional) — does the policy contribute to defense?
  • Interpretation prose — paste-ready summary
  • Full Adversary scorecard — embedded for auditability

Suites are locked

ASB-Browser-v1's 40 attacks will never change. Methodology improvements ship as ASB-Browser-v2. This is the central property that makes scores comparable.

Programmatic API

import { runSuite, ASB_BROWSER_V1, renderMarkdownReport } from '@weave_protocol/agentsecbench';
import { BrowserTarget } from '@weave_protocol/adversary';

const report = await runSuite({
  target: new BrowserTarget({ runAgent }),
  suite: ASB_BROWSER_V1,
  targetMeta: { name: 'My Agent', type: 'browser-agent' },
  measureWardDelta: true,
});
console.log(renderMarkdownReport(report));

Read the full file on GitHub · 70 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. 2d ago First seen · 70 lines · 0 tokens per session scan A ecab3ad567de

Subscribe to this mod's changes

agentsecbench is a skill published in the GitHub repository Tyox-all/Weave_Protocol (0 stars, last pushed 9d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 622 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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