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 agentmods add agents/wishmakingfairy/vibecheck/security-scannergit clone --depth 1 https://github.com/Wishmakingfairy/vibecheckWrote 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/agents/wishmakingfairy/vibecheck/security-scanner)<a href="https://agentmods.dev/agents/wishmakingfairy/vibecheck/security-scanner"><img src="https://agentmods.dev/badge/agents/wishmakingfairy/vibecheck/security-scanner.svg" alt="Measured on agentmods" 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 | $0.00031 | $0.00404 |
| Opus 5 | $0.00015 | $0.00202 |
| Sonnet 5 | $0.00006 | $0.00081 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
security-scanner 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 4d 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.
What it actually says
Security Scanner Agent
Perform a deep security analysis of the entire codebase.
Scan Process
- Stack Detection: Read package.json, requirements.txt, or go.mod to identify the tech stack
- File Discovery: Glob for all source files excluding node_modules, dist, .git, vendor
- Dependency Audit: Run
npm auditorpip auditif available - Source Scan: Read each file and check against all 156 security patterns documented in the reference files
- Cross-File Analysis: Check if auth middleware exists for admin routes, if RLS is enabled for DB tables
- Report Generation: Produce a categorized markdown report sorted by severity
What to Check
For each file, apply the relevant category checks based on file type:
- .js/.ts/.jsx/.tsx: secrets, injection, auth, network, AI/LLM, crypto
- .py: secrets, injection, database, auth, AI/LLM, crypto, filesystem
- .sql: database, secrets
- .json: secrets, supply chain (package.json)
- .yaml/.yml: secrets, infrastructure, supply chain (CI configs)
- .html: injection, headers, supply chain
- Dockerfile: infrastructure, secrets, supply chain
Output Format
Produce a structured report with:
- Summary table (findings by severity per category)
- Detailed findings sorted by severity (CRITICAL first)
- Each finding includes: check ID, file path, line reference, CWE, fix suggestion
- Remediation priority: fix CRITICAL first, then WARNING
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.
- 4d ago First seen · 43 lines · 31 tokens per session scan A f2fc1247c1b9
security-scanner is an agent published in the GitHub repository Wishmakingfairy/vibecheck (4 stars, last pushed 5mo ago), licensed MIT. It adds 31 tokens to every session and 404 once invoked, about $0.0002 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 2026-08-31.
Other agents, from other repositories
tachi-risk-scorer
Quantitative risk scoring agent that enriches threat model findings with four-dimensional scores (CVSS 3.1, exploitability, scalability, reachability), computes weighted composite scores, attaches governance fields, and generates dual-format output (risk-scores.md and risk-scores.sarif).
_AGENT_BEST_PRACTICES
This document provides comprehensive guidance for designing, customizing, and maintaining agents in Agentic Oriented Development Kit.
tachi-threat-report
Transforms structured threat model output into a narrative threat report with executive summary, Mermaid attack trees for Critical and High findings, prioritized remediation roadmap with effort estimates, and complete finding traceability.
tachi-agent-autonomy
Detects threats from autonomous agent systems operating with insufficient constraints on decision-making, action scope, or operational boundaries, including excessive autonomy, goal misalignment, and cascading multi-agent failures.
tachi-data-poisoning
Detects threats where attackers manipulate training data, RAG indexes, knowledge bases, or fine-tuning pipelines to corrupt LLM behavior at the source.
debugger
Bug investigation, root cause analysis using 5 Whys methodology, and systematic troubleshooting. Use for complex debugging sessions and production issue investigation.