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securing-serverless-functions确保无服务器功能的安全

Agent Skill

securing-serverless-functions 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

272

周安装

11

GitHub Stars

5,939

下载量

85
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:securing-serverless-functions(确保无服务器功能的安全)
来源仓库:https://github.com/mukul975/anthropic-cybersecurity-skills
仓库路径:skills/securing-serverless-functions
安装命令:
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill securing-serverless-functions
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill securing-serverless-functions

简介

用于查找、检索和筛选相关信息。

  • 适合根据关键词、任务场景或来源线索快速定位候选结果。
  • 支持 Codex、Claude、Cursor、Gemini CLI,可结合原始 README 进一步验证用途。
  • 安装命令:npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill securing-serverless-functions。
  • 建议确认权限范围和维护状态,避免误触联网或文件操作。

SKILL.md

Securing Serverless Functions

When to Use

  • When deploying Lambda functions or Azure Functions with access to sensitive data or cloud APIs
  • When auditing existing serverless workloads for overly permissive IAM roles
  • When integrating serverless functions into a DevSecOps pipeline with automated security scanning
  • When hardcoded secrets or vulnerable dependencies are discovered in function code
  • When establishing runtime monitoring for serverless workloads to detect injection or credential theft

Do not use for container-based compute security (see securing-kubernetes-on-cloud), for API Gateway configuration (see implementing-cloud-waf-rules), or for serverless architecture design decisions.

Prerequisites

  • AWS Lambda, Azure Functions, or GCP Cloud Functions with deployment access
  • CI/CD pipeline with dependency scanning tools (npm audit, Snyk, Dependabot)
  • AWS Secrets Manager, Azure Key Vault, or HashiCorp Vault for secrets management
  • CloudWatch, Application Insights, or Cloud Logging for function monitoring

Workflow

Step 1: Enforce Least Privilege IAM Roles

Assign each Lambda function a dedicated IAM role with permissions scoped to only the specific resources it accesses. Never share IAM roles across functions.

# Create a least-privilege role for a specific Lambda function
aws iam create-role \
  --role-name order-processor-lambda-role \
  --assume-role-policy-document '{
    "Version": "2012-10-17",
    "Statement": [{
      "Effect": "Allow",
      "Principal": {"Service": "lambda.amazonaws.com"},
      "Action": "sts:AssumeRole"
    }]
  }'

# Attach a scoped policy (not AmazonDynamoDBFullAccess)
aws iam put-role-policy \
  --role-name order-processor-lambda-role \
  --policy-name order-processor-policy \
  --policy-document '{
    "Version": "2012-10-17",
    "Statement": [
      {
        "Effect": "Allow",
        "Action": ["dynamodb:PutItem", "dynamodb:GetItem"],
        "Resource": "arn:aws:dynamodb:us-east-1:123456789012:table/Orders"
      },
      {
        "Effect": "Allow",
        "Action": ["logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents"],
        "Resource": "arn:aws:logs:us-east-1:123456789012:log-group:/aws/lambda/order-processor:*"
      },
      {
        "Effect": "Allow",
        "Action": ["secretsmanager:GetSecretValue"],
        "Resource": "arn:aws:secretsmanager:us-east-1:123456789012:secret:order-api-key-*"
      }
    ]
  }'

Step 2: Eliminate Hardcoded Secrets

Replace plaintext credentials in environment variables with references to secrets management services. Use Lambda extensions or SDK calls to retrieve secrets at runtime.

# INSECURE: Hardcoded credentials in environment variable
# DB_PASSWORD = os.environ['DB_PASSWORD']  # Stored as plaintext in Lambda config

# SECURE: Retrieve from AWS Secrets Manager with caching
import boto3
from botocore.exceptions import ClientError
import json

_secret_cache = {}

def get_secret(secret_name):
    if secret_name in _secret_cache:
        return _secret_cache[secret_name]

    client = boto3.client('secretsmanager')
    response = client.get_secret_value(SecretId=secret_name)
    secret = json.loads(response['SecretString'])
    _secret_cache[secret_name] = secret
    return secret

def lambda_handler(event, context):
    db_creds = get_secret('production/database/credentials')
    db_host = db_creds['host']
    db_password = db_creds['password']
    # Use credentials securely
# Enable encryption at rest for Lambda environment variables
aws lambda update-function-configuration \
  --function-name order-processor \
  --kms-key-arn arn:aws:kms:us-east-1:123456789012:key/key-id

Step 3: Scan Dependencies for Vulnerabilities

Integrate automated dependency scanning into the CI/CD pipeline to catch vulnerable packages before deployment.

# npm audit for Node.js Lambda functions
cd lambda-function/
npm audit --audit-level=high
npm audit fix

# Snyk scanning in CI/CD pipeline
snyk test --severity-threshold=high
snyk monitor --project-name=order-processor-lambda

# pip-audit for Python Lambda functions
pip-audit -r requirements.txt --desc on --fix

# Scan Lambda deployment package with Trivy
trivy fs --severity HIGH,CRITICAL ./lambda-package/
# GitHub Actions CI/CD security scanning
name: Lambda Security Scan
on: [push, pull_request]
jobs:
  security:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Install dependencies
        run: npm ci
      - name: Run npm audit
        run: npm audit --audit-level=high
      - name: Snyk vulnerability scan
        uses: snyk/actions/node@master
        env:
          SNYK_TOKEN: ${{ secrets.SNYK_TOKEN }}
      - name: Scan with Semgrep for code vulnerabilities
        uses: returntocorp/semgrep-action@v1
        with:
          config: p/owasp-top-ten

Step 4: Implement Input Validation

Validate and sanitize all event input data to prevent injection attacks including SQL injection, command injection, and NoSQL injection through Lambda event sources.

import re
import json
from jsonschema import validate, ValidationError

# Define expected input schema
ORDER_SCHEMA = {
    "type": "object",
    "properties": {
        "orderId": {"type": "string", "pattern": "^[a-zA-Z0-9-]{1,36}$"},
        "customerId": {"type": "string", "pattern": "^[a-zA-Z0-9]{1,20}$"},
        "amount": {"type": "number", "minimum": 0.01, "maximum": 999999.99},
        "currency": {"type": "string", "enum": ["USD", "EUR", "GBP"]}
    },
    "required": ["orderId", "customerId", "amount", "currency"],
    "additionalProperties": False
}

def lambda_handler(event, context):
    # Validate API Gateway event body
    try:
        body = json.loads(event.get('body', '{}'))
        validate(instance=body, schema=ORDER_SCHEMA)
    except (json.JSONDecodeError, ValidationError) as e:
        return {
            'statusCode': 400,
            'body': json.dumps({'error': 'Invalid input', 'details': str(e)})
        }

    # Safe to proceed with validated input
    order_id = body['orderId']
    # Use parameterized queries for database operations

Step 5: Configure Function URL and API Gateway Authentication

Secure function invocation endpoints with proper authentication. Never expose Lambda function URLs without IAM or Cognito authentication.

# Secure Lambda function URL with IAM auth (not NONE)
aws lambda create-function-url-config \
  --function-name order-processor \
  --auth-type AWS_IAM \
  --cors '{
    "AllowOrigins": ["https://app.company.com"],
    "AllowMethods": ["POST"],
    "AllowHeaders": ["Content-Type", "Authorization"],
    "MaxAge": 3600
  }'

# API Gateway with Cognito authorizer
aws apigateway create-authorizer \
  --rest-api-id abc123 \
  --name CognitoAuth \
  --type COGNITO_USER_POOLS \
  --provider-arns "arn:aws:cognito-idp:us-east-1:123456789012:userpool/us-east-1_EXAMPLE"

Step 6: Enable Runtime Monitoring and Logging

Configure GuardDuty Lambda Network Activity Monitoring and CloudWatch structured logging to detect anomalous function behavior.

# Enable GuardDuty Lambda protection
aws guardduty update-detector \
  --detector-id <detector-id> \
  --features '[{"Name": "LAMBDA_NETWORK_ACTIVITY_LOGS", "Status": "ENABLED"}]'

# Configure Lambda to use structured logging
aws lambda update-function-configuration \
  --function-name order-processor \
  --logging-config '{"LogFormat": "JSON", "ApplicationLogLevel": "INFO", "SystemLogLevel": "WARN"}'

Key Concepts

TermDefinition
Cold StartInitial function invocation that includes container provisioning, increasing latency and creating a window where cached secrets may not be available
Event InjectionAttack where malicious input is embedded in Lambda event data from API Gateway, S3, SQS, or other event sources to exploit the function
Execution RoleIAM role assumed by Lambda during execution, defining all cloud API permissions the function can use
Function URLDirect HTTPS endpoint for Lambda functions that can be configured with IAM or no authentication (NONE is insecure)
LayerLambda deployment package containing shared code or dependencies that should be scanned for vulnerabilities independently
Reserved ConcurrencyMaximum number of concurrent executions for a function, useful for preventing resource exhaustion attacks
Provisioned ConcurrencyPre-initialized function instances that reduce cold start latency and ensure secrets are cached

Tools & Systems

  • AWS Lambda Power Tuning: Open-source tool for optimizing Lambda memory and timeout settings to balance security with performance
  • Snyk: SCA tool scanning Lambda dependencies for known vulnerabilities with automatic fix suggestions
  • Semgrep: SAST tool with serverless-specific rules detecting injection vulnerabilities, hardcoded secrets, and insecure configurations
  • GuardDuty Lambda Protection: AWS service monitoring Lambda network activity for connections to malicious endpoints
  • AWS X-Ray: Distributed tracing service for detecting suspicious external connections and latency anomalies in Lambda invocations

Common Scenarios

Scenario: SQL Injection via API Gateway to Lambda to RDS

Context: A Lambda function receives user input from API Gateway and constructs SQL queries by string concatenation against an RDS PostgreSQL database. An attacker injects SQL payloads through the API.

Approach:

  1. Audit the Lambda function code for string concatenation in SQL queries
  2. Replace all string-formatted queries with parameterized queries using the database driver
  3. Implement input validation using JSON Schema before any database operation
  4. Add a WAF rule on API Gateway to block common SQL injection patterns
  5. Deploy Semgrep in the CI/CD pipeline with the python.django.security.injection.sql rule set
  6. Enable GuardDuty Lambda protection to detect anomalous database connection patterns

Pitfalls: Relying solely on WAF rules without fixing the underlying code vulnerability allows attackers to bypass with encoding tricks. Using ORM methods incorrectly (raw queries) still allows injection.

Output Format

Serverless Security Assessment Report
=======================================
Account: 123456789012
Functions Assessed: 47
Assessment Date: 2025-02-23

CRITICAL FINDINGS:
  [SLS-001] order-processor: SQL injection via string concatenation
    Language: Python 3.12 | Runtime: Lambda
    Vulnerable Code: f"SELECT * FROM orders WHERE id = '{order_id}'"
    Remediation: Use parameterized queries with psycopg2

  [SLS-002] payment-handler: Hardcoded Stripe API key in environment variable
    Key: sk_live_XXXX... (unencrypted)
    Remediation: Migrate to AWS Secrets Manager with KMS encryption

HIGH FINDINGS:
  [SLS-003] 12 functions share the same IAM execution role with s3:*
  [SLS-004] 8 functions have function URLs with AuthType: NONE
  [SLS-005] 23 functions have dependencies with known HIGH CVEs

DEPENDENCY VULNERABILITIES:
  axios@0.21.1:         CVE-2023-45857 (HIGH) - 5 functions affected
  jsonwebtoken@8.5.1:   CVE-2022-23529 (CRITICAL) - 3 functions affected
  lodash@4.17.15:       CVE-2021-23337 (HIGH) - 11 functions affected

SUMMARY:
  Critical: 2 | High: 5 | Medium: 12 | Low: 8
  Functions with Least Privilege: 14/47 (30%)
  Functions with Secrets Manager: 19/47 (40%)
  Functions with Input Validation: 22/47 (47%)

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.32%
按下载量换算31

Claude

28.86%
按下载量换算25

Cursor

19.39%
按下载量换算16

Gemini CLI

9.71%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

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