Amazon Inspector | Deep Dive.

A deep dive into Amazon Inspector.

Focus:

•        The Concept: Amazon Inspector
•        What Inspector scans / analyzes,
•        Core components & architecture (conceptual),
•        Typical finding schema (what twtech should see),
•        Detection categories and Samples,
•        Integration and automation patterns (practical),
•        Sample automation snippets,
•        Operational runbooks (Samples),
•        Deployment checklist (quick),
•        Tuning and prioritization guidance,
•        Costs & limits (guidance),
•        Limitations & gotchas,
•        Sample Key Performance Indicators (KPIs) & dashboards

1 ,  The Concept: Amazon Inspector

Amazon Inspector is AWS managed service for discovering security issues in twtech AWS workloads.

Amazon Inspector  goals are:

•         Continuously identify vulnerabilities and insecure configurations in instances, images, and serverless functions.
•         Prioritize findings (severity, CVSS, exploitability) and provide actionable remediation guidance.
•         Integrate with AWS automation (EventBridge, Lambda, Systems Manager (SSM)) and Security Event Management (SIEMs) for triage / remediation.
•         There are two generations historically:

•     Inspector Classic
•     Inspector2.

•          Modern usage of Amazon Inspector  is centers around the current, continuously-scanning Inspector service (often called Inspector2)
•         Inspector2 focuses on multi-account continuous scanning, image/Lambda/instance coverage, and centralized findings.

2 ,  What Inspector scans / analyzes

Typical scan targets and telemetry sources:

•         EC2 instances — OS packages, application packages, and optionally an agent-based scan. Agentless scanning is often possible via SSM inventory/insights.
•         Container images in ECR — image layers and packages scanned at push and continuously (image CVEs).
•         Lambda functions — the function package and its dependencies scanned for library/package CVEs.
•         OS/package metadata — NPM/Python/Ruby/JAR/OS package manifests (the service derives SBOM-like inventory).
•         Software configuration checks — CIS benchmark checks and common misconfigurations (depending on enabled checks).
•         Vulnerability intelligence — CVE databases, vendor advisories, and exploitability metadata to rank severity.

3,   Core components & architecture (conceptual)

1.     Collectors / Scanners

•    ECR integration scans images on push and periodically.
•    EC2 scanning via agent or SSM-driven inventory.
•    Lambda scans via packaged dependencies at deployment or during periodic assessment.

2.     Analysis Engine

•    Matches package metadata to CVE databases and rules.
•    Computes severity, CVSS, and provides remediation steps (package fixes, upgrade versions).
•    Deduplicates and groups related findings.

3.     Findings Store

•    Centralized, per-account findings that include metadata: resource id, region, package name/version, CVE, CVSS, remediation, first/last seen.

4.     Publishing / Integration

•    Findings visible in the Inspector console.
•    Forwarding via EventBridge, Security Hub, or via APIs to SIEMs and S3 for archiving.
•    Multi-account aggregation (via Organizations) to enable centralized scanning and reporting.

4,   Typical finding schema (what twtech should see)

A finding generally contains:

•         Finding ID (unique)
•         Resource (EC2 instance id, ECR image digest, Lambda ARN)
•         Finding type (vulnerability, CIS check, configuration)
•         Package / Component (e.g., openssl 1.0.2k)
•         CVE ID(s) (e.g., CVE-YYYY-XXXX)
•         Severity (Low / Medium / High / Critical)
•         Common Vulnerability Scoring System (CVSS) numeric.
•         Exploitability / Public exploit evidence (if known)
•         Remediation steps (update package to X, replace image, apply patch)
•         Timestamps (first seen, last seen)
•         Account & Region metadata

5,   Detection categories and Samples

•         Package CVEs: outdated library with known CVE.
•         OS-level vulnerabilities: kernel / system libraries needing patch.
•         Container image vulnerabilities: insecure base images, outdated packages.
•         Function vulnerabilities: vulnerable runtime dependencies in Lambda zip/layers.
•         Configuration / Policy checks (when enabled): missing hardening controls, insecure permissions.
•         Package misconfiguration: e.g., a web server exposing debug endpoints.

6,   Integration and automation patterns (practical)

•         EventBridge → Lambda: route Inspector findings by severity to Lambda for triage (create ticket, notify Slack/SysOps, or start remediation).
•         Inspector → Security Hub: centralize findings and use Security Hub insights/playbooks.
•         Inspector → SIEM / S3: export to SIEM for long-term correlation; export to S3 for retention and offline analytics.
•         Auto-remediation with SSM: for EC2, use SSM Run Command or Patch Manager to apply updates automatically for low-risk fixes.
•         CI/CD gate: block image promotion when ECR image scan reports critical CVEs; integrate with CodePipeline or scanning step.
•         Shift-left: run static scanning in build pipelines against the same CVE database sets to catch issues before deployment.

7,   Sample automation snippets (conceptual — adapt names)

Below are illustrative patterns you can copy/paste and adapt.

# EventBridge rule (pseudo-JSON) to capture high/critical Inspector findings:

# json

{

  "source": ["aws.inspector2"],

  "detail-type": ["Inspector2 Finding"],

  "detail": {

    "severity": [{"numeric": [">=", 7.0]}],

    "status": ["ACTIVE"]

  }

}

# Lambda handler (Python) to auto-initiate remediation on EC2 via SSM:

# python

import boto3

import twtech

ssm = boto3.client('ssm')

inspector = boto3.client('inspector2')  # or use event payload

def lambda_handler(event, context):

    finding = event['detail']

    resource = finding['resource']['id']

    # Example: trigger SSM Run Command to update packages

    response = ssm.send_command(

        InstanceIds=[resource],

        DocumentName='AWS-RunPatchBaseline',  # or custom patch document

        Parameters={'Operation': ['Install']}

    )

    # Persist or ticket the run_command id for audit

    return {'status': 'started', 'command_id': response['Command']['CommandId']}

NB:

Adapt detail parsing and event source names for your environment. Always test in staging.

8,   Operational runbooks (Samples)

A. High-severity CVE on EC2 (playbook)

1.     Alert: EventBridge triggers SOC channel and creates a ticket.

2.     Triage: Validate finding — confirm instance, package, and confirm whether exploit in environment (public exposure, open ports).

3.     Contain (if exploited or exposed): isolate ENI (move to quarantine subnet / update NACLs), stop instance if needed, snapshot disks (for forensics).

4.     Remediate:

o   Preferred: patch via SSM Run Command / Patch Manager (apply updates).

o   If patch unavailable: replace instance via image build with patched AMI.

5.     Verify: Re-scan with Inspector to confirm fix; monitor for recurrence.

6.     Post-mortem: root cause analysis (incident review, retrospective, or lessons learned); update CI/CD to prevent reintroduction.

B. Critical CVE in ECR image (playbook)

1.      Block promotion of this image (CI/CD).
2.      Rebuild image with patched base image or updated dependency.
3.      Retest container, re-run image scan and integration tests.
4.      Deploy patched image to production following canary/blue-green.
5.      Deprecate (or delete) old image tags and update image lifecycle policies.

9,   Deployment checklist (quick)

•         Enable Inspector across accounts (use Organizations for delegated admin).
•         Configure ECR image scanning on push and scheduled scanning.
•         Ensure EC2 inventory/SSM agent coverage for agentless scanning where possible.
•         Enable Lambda scanning for functions.
•         Hook Inspector findings into EventBridge and Security Hub.
•         Configure retention/export (S3 or SIEM).
•         Define automated playbooks for critical/urgent severities.
•         Define a patch policy and test SSM remediation runbooks.

10,   Tuning and prioritization guidance

•         Tune scanning cadence: frequent enough for your risk posture, mindful of quotas.
•         Prioritize by exploitability: CVSS + presence of public exploit code + internet exposure.
•         Group findings: use grouping by package + CVE to reduce noise.
•         Suppress / mark as accepted: document compensating controls for false-positives (e.g., immutable read-only environments).
•         Shift-left: integrate image/library scanning into dev pipelines to reduce production churn(vulnerabilities).

11,   Costs & limits (high-level guidance)

•         Expect costs from: image scan counts, API calls, multi-account aggregated scanning, and data export. Tuning scanning frequency and limiting non-critical accounts helps.
•         Use lifecycle policies in ECR and selective scanning if cost-constrained.

12,   Limitations & gotchas

•         Not a full runtime EDR: Inspector finds vulnerabilities in artifacts and configurations; it’s not a behavioral endpoint detection product (use alongside EDR solutions).
•         Coverage variance: scanning quality depends on whether you use agent or agentless methods and whether the package metadata is visible.
•         False positives: package metadata mismatch or custom-built packages without upstream CVE mapping may show ambiguous findings.
•         Remediation complexity: some vulnerable libraries are transitive dependencies; remediation may require code changes or dependency upgrades.

13,   Useful SOC metrics to track

•         Time-to-detect (TTD) — time between vulnerability disclosure and detection in your estate.
•         Time-to-remediate (TTR) — measured per severity bucket.
•         Number of critical/active findings (trend).
•         Percentage of images failing scan at build-time vs production-time.
•         Patch compliance rate (by baseline).

14, Sample Key Performance Indicators (KPIs) & dashboards

•         Weekly count of newly detected critical CVEs across accounts.
•         Mean days to remediate (critical/important).
•         ECR image pass rate at push.
•         EC2 instances missing SSM coverage.