Security Review Spec logo

Security Review Spec

Organization
warpdotdev
security-review-spec

Audit a product or tech spec pull request diff for high-level security concerns (threat surface, authentication and authorization model, trust boundaries, sensitive data handling, secrets and key management, dependency posture, and abuse or misuse cases) and fold findings into the same review.json produced by the base spec review. Use as a supplement to `review-spec` whenever a spec PR is being reviewed.

Overview

Publisherwarpdotdev
Repositoryoz-for-oss
Skill namesecurity-review-spec
Stars
313
Forks
43
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by warpdotdev on GitHub. Read the source before you install it.

Installation

Install the Security Review Spec AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/warpdotdev/oz-for-oss/tree/main/.agents/skills/security-review-spec
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/warpdotdev/oz-for-oss.git /tmp/oz-for-oss
mkdir -p .claude/skills
cp -r /tmp/oz-for-oss/.agents/skills/security-review-spec .claude/skills/security-review-spec
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Security Review Spec in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Security Review Spec on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Security Review Spec is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Security Review Spec Skill

Audit the current spec pull request for security concerns at the design-doc level and fold any findings into the same review.json produced by the base review-spec skill.

Goal

Provide a focused security pass on top of the general spec review. This is a supplement to review-spec, not a separate output. Findings must be merged into the single combined review.json so reviewers receive one cohesive review.

The focus here is high-level design concerns that a security-minded reader would raise on a product or tech spec, not line-by-line code issues. Flag gaps, ambiguities, or design choices that would plausibly lead to an insecure implementation if built as described.

Inputs

  • The working directory is the PR branch checkout.
  • The workflow usually provides an annotated diff in pr_diff.txt.
  • The workflow usually provides the PR description in pr_description.md.
  • Spec PRs typically only modify files under specs/.
  • Focus on the spec files and sections changed by this PR.
  • Default behavior: do not post comments or reviews to GitHub directly.

When to apply this skill

  • Apply on spec PRs whenever review-spec is applied.
  • Do not apply on code PRs handled by review-pr; those use security-review-pr instead.
  • Skip the skill entirely when the changed spec content has no plausible security surface (e.g. purely editorial wording changes, typo fixes, or doc structure cleanup). It is better to stay silent than to manufacture findings.
  • Do not duplicate findings the base review-spec pass will already raise. If the base review would naturally catch an issue, leave it there rather than re-reporting it from the security pass.

Security concerns to audit

Evaluate the changed spec content against the following concerns. Treat the list as a checklist, not a ceiling — flag other clearly security-relevant design issues when they appear. Stay at the design-doc level: worry about what the spec does or does not commit to, not how it will be coded.

Threat surface and trust boundaries

  • New external inputs, endpoints, webhooks, CLI surfaces, or file formats that are introduced without describing who can reach them and under what trust assumptions.
  • Trust boundaries that are implied but not explicitly stated (e.g. "the agent receives data from GitHub" without saying which fields are attacker-controlled).
  • User-supplied or third-party content (issues, comments, spec bodies, uploaded files, remote URLs) that will flow into automation, prompts, commands, or storage without a clear validation or sanitization plan.
  • Features that expand what an unauthenticated or low-privilege actor can cause the system to do.

Authentication and authorization model

  • New actors, roles, or automation identities introduced without a clear description of how they authenticate and what they are allowed to do.
  • Authorization rules that are described informally ("only maintainers can trigger this") without specifying how that is enforced.
  • Privilege escalation risks: features where a less-privileged user can cause a more-privileged actor (bot, workflow, agent) to act on their behalf without explicit gating.
  • Missing discussion of how permission or ownership changes propagate (e.g. revoking access, rotating tokens, removing a collaborator).

Sensitive data handling and privacy

  • New data the system will collect, store, log, or transmit without stating sensitivity, retention, or access controls.
  • Personally identifiable information, auth tokens, session identifiers, private repository contents, or customer data routed through logs, analytics, prompts, or third-party services without a redaction plan.
  • Specs that assume data is "internal" without describing the boundary that keeps it internal.
  • Missing discussion of how the feature behaves for private repositories, restricted orgs, or data subject to deletion requests.

Secrets and key management

  • New credentials, API keys, signing keys, or tokens introduced without describing where they live, who can read them, and how they are rotated.
  • Specs that describe passing secrets through environment variables, command-line arguments, or log-visible paths without acknowledging the exposure.
  • Shared secrets across environments (dev, staging, prod) where the spec does not call out isolation.
  • Missing discussion of what happens when a secret is leaked or revoked.

Abuse, misuse, and denial of service

  • Features that can be triggered by external events (webhooks, comments, scheduled jobs) without describing rate limiting, deduplication, or cost controls.
  • Automation loops where attacker-controlled input can cause unbounded work, recursive invocations, or expensive downstream calls.
  • Agent or LLM-driven flows where untrusted input can be interpreted as instructions (prompt injection) without a mitigation described in the spec.
  • Missing discussion of what happens under partial failure (retries, duplicate side effects, poisoned queues).

Dependencies and supply chain

  • New third-party services, registries, models, or binaries introduced without describing trust assumptions or pinning strategy.
  • Plans to execute code or scripts fetched at runtime (remote scripts, downloaded binaries, dynamic imports) without integrity verification.
  • Vendor or tool choices that materially change the repository's trust boundary without calling that out.

Configuration and defaults

  • New configuration options or feature flags whose default value is insecure (auth optional, TLS off, public by default) without explicit justification.
  • Specs that leave important defaults unspecified when the safe choice is not obvious.
  • CORS, cookie, header, or file-permission decisions implied by the design but not written down.

Observability and incident response

  • Specs that introduce security-relevant operations (auth, secret use, privileged actions) without describing what is logged, how logs are protected, and how an operator would notice abuse.
  • Missing discussion of how to detect and respond to the specific failure modes introduced by the feature.

Process

  1. Read pr_description.md and pr_diff.txt to understand the scope and intent of the spec change.
  2. For each changed section, ask: if this were implemented as written, which of the concerns above would a security-minded reviewer raise?
  3. Distinguish between "the spec is silent on X" (usually flag) and "the spec explicitly accepts risk X" (usually acceptable if the reasoning is sound).
  4. Prefer evidence-based findings tied to specific changed lines or sections. If a concern only applies to untouched spec content, describe it in the review summary instead of as an inline comment.
  5. Do not flag purely editorial or non-security issues here — those belong in the base review-spec pass.
  6. Do not repeat findings already covered by the base review; if the base pass would naturally catch it, leave it there.
  7. Do not treat a spec as insecure just because it does not exhaustively enumerate every threat. Focus on concerns that would plausibly lead to an insecure implementation or a missed mitigation.

Outputs

  • Do not create a separate report file.
  • Fold security findings into the same review.json produced by review-spec.
  • Prefix every security finding's comment body with a [SECURITY] tag after the severity label so reviewers can tell the source of the concern. For example:
    • 🚨 [CRITICAL] [SECURITY] Spec allows untrusted input into shell command without validation: ...
    • ⚠️ [IMPORTANT] [SECURITY] Authentication model for new webhook is unspecified: ...
    • 💡 [SUGGESTION] [SECURITY] Consider documenting token rotation strategy: ...
  • In the review summary, add a dedicated ## Security subsection when there are security findings. List the most important security concerns there in addition to any inline comments. If there are no security findings, do not add the subsection.
  • Count security findings toward the existing Found: X critical, Y important, Z suggestions tally in the summary. Do not add a separate security counter.
  • Upgrade the overall verdict if a security finding materially demands it. A critical security finding in a spec should generally result in Request changes so the design gap is resolved before implementation.

Severity mapping

  • 🚨 [CRITICAL] for design choices that would almost certainly produce an exploitable implementation (e.g. feeding untrusted issue bodies directly into a shell command, auth explicitly optional on a destructive action, storing plaintext credentials).
  • ⚠️ [IMPORTANT] for design gaps that should be resolved before implementation (e.g. missing authentication model for a new surface, unspecified handling of private-repo data, absent rate limiting on an externally triggerable flow).
  • 💡 [SUGGESTION] for defense-in-depth improvements or documentation gaps that would strengthen the spec but are not blockers (e.g. calling out token rotation, documenting log redaction).
  • 🧹 [NIT] is rarely appropriate for security findings; use only when the comment includes a concrete rewrite and the issue is genuinely cosmetic.

Inline comment requirements

  • Follow the same diff-line rules as review-spec: inline comments must target lines that exist in this PR's diff.
  • Keep comments concise, direct, and actionable. Explain the concern, then the fix the spec should adopt.
  • When proposing a concrete spec rewrite, use the same suggestion block format as review-spec.

Boundaries

  • Do not perform code-level review; this skill is scoped to spec prose and design decisions.
  • Do not run dynamic scans, fetch remote advisories, or call external security APIs.
  • Do not speculate about vulnerabilities that cannot be tied to the diff or the checked-out spec files.
  • Do not gate the PR on theoretical risks; prefer 💡 [SUGGESTION] when the risk is low or the mitigation is optional.
  • Do not post to GitHub directly. Your only output is the merged review.json from the base review pass.

Frequently asked questions

What does the Security Review Spec AI skill do?

Audit a product or tech spec pull request diff for high-level security concerns (threat surface, authentication and authorization model, trust boundaries, sensitive data handling, secrets and key management, dependency posture, and abuse or misuse cases) and fold findings into the same review.json produced by the base spec review. Use as a supplement to `review-spec` whenever a spec PR is being reviewed.

Why use Security Review Spec on TypingMind?

Because you install it once and use it with any model. Security Review Spec is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Security Review Spec in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/warpdotdev/oz-for-oss/tree/main/.agents/skills/security-review-spec. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Security Review Spec?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Security Review Spec?

As many as you like. As long as a model supports skills, you can use Security Review Spec with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Security Review Spec AI skill free?

Yes. It is published on GitHub by warpdotdev under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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