Application AI Guardrail Config Tampering logo

Application AI Guardrail Config Tampering

Organization
CDESpace
Application AI Guardrail Config Tampering

Triage an alert where an AI system's guardrails, permissions, or credential path are weakened through its configuration, agent settings granting wildcard or blanket tool permissions, disabling approval or confirmation prompts, redirecting the credential or API-key helper to an external script, downgrading model safety or guardrail settings, or widening an agent's tool or domain allowlist. Reads the actor, the direction of the change, and whether it is routine config management, to tell sanctioned administration apart from someone removing the brakes on an AI system, and decides escalate or dismiss.

Overview

PublisherCDESpace
RepositoryDetection-Skills
Skill nameApplication AI Guardrail Config Tampering
Stars
57
Forks
5
Bundled files
Instructions only
LicenseApache-2.0
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 CDESpace on GitHub. Read the source before you install it.

Installation

Install the Application AI Guardrail Config Tampering 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/CDESpace/Detection-Skills/tree/main/skills/triage/application-ai-guardrail-config-tampering
  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/CDESpace/Detection-Skills.git /tmp/Detection-Skills
mkdir -p .claude/skills
cp -r /tmp/Detection-Skills/skills/triage/application-ai-guardrail-config-tampering .claude/skills/cdespace-application-ai-guardrail-config-tampering
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Application AI Guardrail Config Tampering 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 Application AI Guardrail Config Tampering 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 Application AI Guardrail Config Tampering 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.

Triage Steps

This class fires on configuration changes to an AI system that are normal admin work by themselves, editing an agent's settings, adjusting a permission, updating a guardrail. Teams tune these every week, so the fact that a config changed is not the signal. The signal is the direction and the actor: a change that removes a safety, a blanket tool permission, approval prompts turned off, a credential helper pointed at an arbitrary script, a model guardrail loosened, made by someone who does not own that configuration. An attacker who reaches an AI system's config weakens it so later actions run unseen and unchecked. Triage here is reading who made the change and whether it opens the system up. This class owns the configuration change itself; an untrusted instruction file that carries execution content is judged by Application AI Prompt Injection, and adding a whole new tool is judged by Application AI Tooling Supply Chain.

Begin with this detection's track record on this actor and system, a rule that fires when the platform team tunes agent settings and is always closed benign starts the call near dismiss, then read the leads below. None is required on its own; they stack, and a single strong one (approval prompts disabled by an unexpected actor) can carry the call.

Leads that point to a real threat, what to look for in the data:

  • A blanket permission granted. Agent settings widened to a wildcard or unrestricted tool grant, a Claude Code settings.json permission such as Bash(*) or a bare "*", or an equivalent allow-all in a Cursor or agent config, handing the agent unconstrained capability.
  • Approvals or confirmations turned off. A change that removes the human check before an agent acts, a default mode set to bypass permissions, auto-approve or "always allow" enabled, an interactive confirmation disabled, so subsequent actions run without a prompt.
  • The credential path redirected. An apiKeyHelper or equivalent credential/API-key helper pointed at an external or newly written script, or a model endpoint or base URL swapped, routing the system's authentication or traffic through attacker-controlled code.
  • A guardrail or allowlist loosened. A model safety or content guardrail downgraded or deleted (for example a Bedrock DeleteGuardrail or a guardrail UpdateGuardrail that removes filters), or an agent's tool or domain allowlist widened to permit destinations it previously blocked.

Leads that rule it out, benign context you can actually see in the data; if the data doesn't show it, you don't have it:

  • A confirmed owner whose role fits. The actor is a known platform or AI-system admin whose role and prior history include this exact change, confirmed in the identity directory, not assumed from the account name.
  • A known automation identity. A documented infrastructure-as-code or deployment service account with a steady baseline of these config edits, the platform maintaining itself.
  • The change tightens, not loosens. A permission narrowed, a guardrail added, approvals enabled, hardening is hygiene, not this threat.
  • Baseline and window. The same setting, actor, and change shape have run here before inside a known maintenance or change window.
  • Clean history. This rule has closed benign on this actor before, with nothing new about who acted or which protection was touched this time.

To confirm a lead instead of guessing, pull the thread: after the config was weakened, did the same actor take an agent action that the removed guardrail would have caught, or make further loosening changes in the same window? Corroboration turns a suspicious config edit into a confirmed one.

Output

Decision

  • escalate: a blanket tool permission, approvals turned off, the credential path redirected, or a guardrail or allowlist loosened by an actor who does not own the configuration, especially two together, or any one followed by an agent action the guardrail would have blocked.
  • dismiss: a confirmed owner or known automation identity, acting inside a known window with a baseline match, explains it, and the change tightens rather than loosens, or a current, approved change owned by a confirmed owner or known automation identity accounts for the loosening. A dismiss is a positive call that the change is benign, made with that context in hand, an owner you confirmed in the directory, a window or baseline you actually saw the change fit; an actor you couldn't resolve or a change you couldn't place is not that context, and absence of a bad sign is not proof it's good. Dismiss is logged and reopenable; when an unexpected actor removes a safety, redirects credentials, or widens permissions, escalate.

Evidence

The setting changed and the direction (toward less or more restriction), the actor and whether they are a confirmed owner, known automation, or unexpected, whether a credential helper or endpoint was redirected, the change window and baseline, any agent action that followed, and how this rule was handled here before.

Reasoning

Name the leads that decided it and how they stacked, an apiKeyHelper redirected to a newly written script by an ordinary user, followed by agent activity, is escalate on its own; a platform service account narrowing a permission on its usual cadence is dismiss.

Frequently asked questions

What does the Application AI Guardrail Config Tampering AI skill do?

Triage an alert where an AI system's guardrails, permissions, or credential path are weakened through its configuration, agent settings granting wildcard or blanket tool permissions, disabling approval or confirmation prompts, redirecting the credential or API-key helper to an external script, downgrading model safety or guardrail settings, or widening an agent's tool or domain allowlist. Reads the actor, the direction of the change, and whether it is routine config management, to tell sanctioned administration apart from someone removing the brakes on an AI system, and decides escalate or...

Why use Application AI Guardrail Config Tampering on TypingMind?

Because you install it once and use it with any model. Application AI Guardrail Config Tampering 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 Application AI Guardrail Config Tampering in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CDESpace/Detection-Skills/tree/main/skills/triage/application-ai-guardrail-config-tampering. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Application AI Guardrail Config Tampering?

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 Application AI Guardrail Config Tampering?

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

Is the Application AI Guardrail Config Tampering AI skill free?

Yes. It is published on GitHub by CDESpace under the Apache-2.0 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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