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Aws Secrets Manager

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aws
aws-secrets-manager

Secret safety for AWS Secrets Manager, secret management, credentials, API keys, tokens, and passwords. Prevents AI agents from directly fetching secret values and teaches runtime dynamic references with asm-exec so plaintext never enters the LLM context window.

Overview

Publisheraws
Repositoryagent-toolkit-for-aws
Skill nameaws-secrets-manager
Stars
2.7K
Forks
311
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Aws Secrets Manager 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.
  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/aws/agent-toolkit-for-aws.git /tmp/agent-toolkit-for-aws
mkdir -p .claude/skills
cp -r /tmp/agent-toolkit-for-aws/plugins/aws-core/skills/aws-secrets-manager .claude/skills/aws-secrets-manager
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aws Secrets Manager 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 Aws Secrets Manager 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 Aws Secrets Manager 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.

Using Secrets Safely with Agents

Overview

When AI agents handle secrets, credentials, API keys, tokens, or passwords with shell or AWS API access, they can call aws secretsmanager get-secret-value and receive plaintext values in their context window. This creates risk: secrets may leak into logs, conversation history, or downstream tool calls.

This skill teaches a safer pattern: dynamic references resolved at runtime by a wrapper script (asm-exec), so the agent never sees the secret value.

Best-effort defense, not a security boundary. This prevents the most common leakage path but cannot stop all evasion vectors. Combine with IAM least-privilege, CloudTrail monitoring, and VPC endpoint policies.

Rules

You MUST follow these rules when working with secrets:

  1. MUST NOT call get-secret-value or batch-get-secret-value -- not via AWS CLI, SDK, MCP tools, curl, or any other mechanism.
  2. MUST NOT attempt to read secret values from the Secrets Manager Agent (SMA) daemon directly (localhost:2773 or any loopback variant).
  3. MUST use {{resolve:secretsmanager:...}} references -- these are resolved at runtime by asm-exec without exposing values to you.

The {{resolve:...}} Syntax

{{resolve:secretsmanager:<secret-id>:<field-type>:<json-key>:<version-stage>}}
ComponentRequiredDefaultExample
secret-idYes--prod/db-creds or full ARN
field-typeNoSecretStringSecretString
json-keyNo(full value)password
version-stageNoAWSCURRENTAWSPENDING

Using asm-exec

asm-exec is a wrapper that resolves {{resolve:...}} references in command arguments and environment variables, then execs the target command. The secret value exists only in the child process -- never in the agent's context.

Usage

bash
# Pass a database password to psql without exposing it
asm-exec -- psql \
  "host=mydb.example.com \
   user={{resolve:secretsmanager:prod/db-creds:SecretString:username}} \
   password={{resolve:secretsmanager:prod/db-creds:SecretString:password}}" \
  -c "SELECT * FROM users LIMIT 10"

# Use default field-type (SecretString) and full value (no json-key)
asm-exec -- curl -H "Authorization: Bearer {{resolve:secretsmanager:prod/api-token}}" \
  https://api.example.com/data

# Multiple secrets in one command
asm-exec -- mysql \
  -h {{resolve:secretsmanager:prod/mysql:SecretString:host}} \
  -u {{resolve:secretsmanager:prod/mysql:SecretString:username}} \
  -p{{resolve:secretsmanager:prod/mysql:SecretString:password}} \
  -e "SHOW TABLES"

How It Works

  1. Scans all command arguments for {{resolve:...}} patterns
  2. Resolves each reference through the first available backend, in order:
    1. AWS Secrets Manager Agent (SMA) on localhost:2773 (zero-latency, cached)
    2. AWS MCP endpoint (https://aws-mcp.us-east-1.api.aws/mcp), calling the aws___run_script tool over a SigV4-signed request (the tool runs a short server-side Python script that fetches the secret via call_boto3)
    3. Determines the secret's region from an ARN's region segment, or from AWS_REGION / AWS_DEFAULT_REGION, and passes it to the resolver
  3. Substitutes resolved values using re.sub with a callable (single-pass -- prevents re-scan injection if a secret value contains {{resolve:...}})
  4. Runs the target command via subprocess.run -- secret values exist only in the asm-exec process, never in the agent's context window

No local AWS CLI fallback for resolution. asm-exec does not shell out to aws secretsmanager get-secret-value to resolve references. Resolution happens only through SMA or the MCP endpoint, so the plaintext value is never written to a local process's stdout where it could be captured.

SigV4 signing

The MCP endpoint authenticates every tool call with AWS SigV4. asm-exec signs requests itself using only the Python standard library (hashlib/hmac) -- it does not depend on botocore or spin up the mcp-proxy-for-aws-cli proxy, keeping the wrapper a lightweight ephemeral process. The signing service and region are inferred from the endpoint hostname (e.g. aws-mcp.us-east-1.api.aws -> service aws-mcp, region us-east-1); this signing region is independent of the secret's own region, which is passed as the region_name argument to the server-side call_boto3 call.

Credentials for signing are resolved in order: environment variables (AWS_ACCESS_KEY_ID etc.), aws configure export-credentials (AWS CLI v2), then aws configure get (AWS CLI v1).

Prerequisites

Either backend must be reachable, with credentials that have secretsmanager:GetSecretValue permission:

  • AWS Secrets Manager Agent (SMA) running on localhost:2773, OR
  • AWS credentials resolvable for SigV4 signing of the MCP endpoint (see above). For cross-region secrets, set AWS_REGION (or use a full ARN) so the correct region is targeted.

See SMA setup guide.

Common Patterns

Database connections

bash
asm-exec -- psql "postgresql://{{resolve:secretsmanager:prod/db:SecretString:username}}:{{resolve:secretsmanager:prod/db:SecretString:password}}@db.example.com:5432/mydb"

Docker with secrets

bash
asm-exec -- docker run -e "DB_PASSWORD={{resolve:secretsmanager:prod/db:SecretString:password}}" myapp:latest

Configuration file templating

bash
# Generate config with resolved secrets, write to file
asm-exec -- sh -c 'echo "password={{resolve:secretsmanager:app/db:SecretString:password}}" > /tmp/app.conf'

Structural Enforcement (Plugin Hook)

When the aws-core plugin is enabled, a PreToolUse hook automatically blocks any attempt to call get-secret-value or batch-get-secret-value -- via AWS CLI, MCP tools, or direct SMA access. No manual configuration needed.

The hook is defined at plugins/aws-core/com.anthropic.claude-code/hooks/hooks.json and activates automatically when the plugin is installed.

Troubleshooting

"Secret not found" errors

Verify the secret exists and your IAM role has secretsmanager:GetSecretValue permission. Check the secret name matches exactly (case-sensitive).

SMA connection refused

The Secrets Manager Agent may not be running. This is non-fatal: asm-exec falls through to the SigV4-signed MCP endpoint. Ensure AWS credentials are resolvable (see SigV4 signing above) so that backend can authenticate.

"Failed to resolve" errors

Both backends were unreachable or returned no value. When MCP resolution fails, asm-exec prints the specific cause to stderr (asm-exec: MCP resolution failed: ...) -- a timeout, an unreachable endpoint, an HTTP status, a denied permission, or a missing value -- so read that line first. Check that either SMA is running or AWS credentials are valid (aws sts get-caller-identity), that the secret's region is correct (set AWS_REGION or use a full ARN), and that your identity has secretsmanager:GetSecretValue on the secret. A 401 from the MCP endpoint indicates a SigV4 signing or credential problem, not a missing secret. If the failure is a timeout, the server-side call may need longer than the default 30s -- raise it with ASM_EXEC_MCP_TIMEOUT (seconds).

Resolution produces empty string

The JSON key may not exist in the secret value. Verify the secret structure in the AWS Console or ask the secret owner to confirm the available keys.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Aws Secrets Manager AI skill do?

Secret safety for AWS Secrets Manager, secret management, credentials, API keys, tokens, and passwords. Prevents AI agents from directly fetching secret values and teaches runtime dynamic references with asm-exec so plaintext never enters the LLM context window.

Why use Aws Secrets Manager on TypingMind?

Because you install it once and use it with any model. Aws Secrets Manager 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 Aws Secrets Manager in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-core/skills/aws-secrets-manager. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Aws Secrets Manager?

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 Aws Secrets Manager?

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

Is the Aws Secrets Manager AI skill free?

Yes. It is published on GitHub by aws 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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