Wednesday, December 4, 2019 completetly rebuilded

To improve performance and service scalability was completely rebuild leveraging aws native services and serverless approach.

Now service:
  • support both http and https
  • has dedicated scanning endpoint:
  • has a human readable website:
  • scanning endpoint now api driven and will support rest api calls for advanced functionality
  • serverless and scalable
Main functionality so far unchanged: 
What it does? TCP Scan of you external IP.
What it scanning for: 100 most used tcp ports. Actually a bit more than 100 - I'm slowly adding more ports.
How to use: simply curl from your console/terminal or open it in browser or visit will trigger scan)
How fast: whole scan takes about a second. Results for each requester IP are cached for 1 hour to reduce load and prevent abuse.

Why? Needed quick way to check open ports on server/gateway/fw/router while being inside the console.

Saturday, May 4, 2019

Awesome list of Native AWS logging capabilities

While looking on centralized logging  capabilities of AWS and going trough bunch of documentation, I noticed lack of the one "big table" where I can find all AWS native logging capabilities per each service and up-to-date service coverage for AWS cloudwatch logs service.
Building I big table is not really version control friendly, so please welcome:

Awesome list of Native AWS logging capabilities:

While I was building this list, some service have already changed their capabilities causing some information in the list being out-of-sync.
 I'll try my best to regularly review existing services and keep adding new one, but if you find mistake or would like to contribute feel free to contact me or create a PR.

Friday, April 12, 2019

Using Terraform to create project and users required in GCP and GSuite

This article is more like quick HOWTO/QuickNote page to start using Terraform with GCP, grant required permission, connect Terraform to GSuite and create users and projects using Terraform.

Connect Terraform to GCP:

1. Download and install Google Cloud SDK:

2. Initialize SDK gcloud init 
 This process will launch browser-based authorization flow

3. Use browser to create  project, service account and download credentials: Note: You need to have GCP billing account and payment method configured first. You can use cli as well:

gcloud projects list
gcloud beta billing accounts list
gcloud beta billing projects link infosec-gcp --billing-account 01122-74525-1222
gcloud config list
gcloud iam service-accounts create infosec-terraform --display-name "Infosec Terraform admin account"
gcloud iam service-accounts keys create ~/.config/gcloud/infosec-terraform-admin.json --iam-account

4. Give appropriate permissions to the Terraform:
get you organization id
gcloud organizations list

Enable iam api (yes you need to enable each api set you are planning to use with GCP, they are disabled by default) you can check what services are enabled using gcloud services list --available
gcloud services enable

Check existing IAM policies in you org:
gcloud organizations get-iam-policy ORGANIZATION_ID

Grant all required permissions(example):
gcloud organizations add-iam-policy-binding ORGANIZATION_ID --member --role roles/resourcemanager.projectCreator

gcloud organizations add-iam-policy-binding ORGANIZATION_ID --member --role roles/billing.user

gcloud organizations add-iam-policy-binding ORGANIZATION_ID --member --role roles/owner

5. Start using terraform from my example to create project and grant access to it.

The only missing part is actually users.
Connecting Terraform to GSuite:

Why do we need GSuite at all? GCP does not provide you any built-in identity and rely on the user identities from Gmail, GSuite or Google Cloud Identity (+ service accounts)

As AWS user I do really love to have user/groups management and infra/project creation using the same automation tool. Unfortunately, user/GSuite functionality is not provided by GCP Terraform provider. Luckily, there is pretty nice open-sourced Terraform provider for GSuite writtend by DeviaVir:
At the moment when I tested it, some group membership functionality was still lacking idempotency, but  using the way from my example everything started to work like a charm.

So the code finally:

Way more details and examples are in the articles below :

Tuesday, February 26, 2019

Revamping AWS APIs' security review and SCP policy generation process.

AWS Cloud provides endless amount of the capabilities and services. Unleashing all this power on the without proper security review process is extremely risky.
Each service and quite often even each api call should be reviewed and evaluated according to the organizational security standards  and compliance requirements. Yes, but.. curently AWS has about 170 services and endless amount of APIs. AWS constantly evolves, introduce new services, APIs and modifying existing.
One of the biggest challenge for me was finding a way to automatically fetch up-to-date annotated  list of the services and api provided by AWS. Luckily, Matt Weagle suggested to use AWS GO SDK as a source of truth. This SDK provides well documented lists of the AWS APIs (docs-2.json)

I crafted small python program that builds/updates following yaml files (one per each service) using json files as a source:

  description: Assess, monitor, manage, and remediate security issues across your
    AWS infrastructure, applications, and data.
  links: []
  security_risk: Cloud IDS
  - Prod_en
  - none
  description: Accepts the invitation to be monitored by a master GuardDuty account.
  links: []
  security_risk: should be allowed only from trusted accounts
  - none
  - none
  description: Archives Amazon GuardDuty findings specified by the list of finding
  links: []
  security_risk: Not defined
  - none
  - none

Structure of this file is quite self-explanatory and simplifies security review(still manual process) of the AWS APIs. During security review,  you specify which services/api are enabled/disabled and on which environments by adding environment name to the Allowed_on  and Denied_on lists. Files are stored in the git repo.

After the review, using these files as a source of truth, I (actually another python program) generate an SCP (Service Control Policy) for AWS Organization's accounts, IAM policies and permission boundaries (it depends on the case.)
Due to the very strict SCP size restrictions , generating this policy using automation allows you:

  • aggregate APIs using wildcards to reduce SCP size
  • validate API wildcards preventing unintentional service exposure/blockage
  • perform cross check for the API to avoid whitelisting/blacklisting conflicts
  • re-generate/validate SCP if AWS introduces new API calls/services
Everything mentioned above is valid not only for the SCP, but for the IAM policy/permission boundaries generation process.

This automated approach opens another possibility - automated compliance validation for AWS: using the same yaml files as a source of truth ,  perform API calls to the AWS to ensure that these calls will fail. This step could be done after deployment (to validate deployment) or on a regular basis(audit).

PS. Unfortunately code of the tools can't be open-sourced as of now.