The Attacks That Made Me Rethink Everything

Look, I used to think supply chain attacks were this theoretical thing that happened to other people. Then SolarWinds got hit, and suddenly I'm spending my weekends auditing every build script we've ever written.

SolarWinds (2020) - The One That Woke Everyone Up

SLSA Supply Chain Threats Diagram

This one still keeps me up at night. Russian state hackers got into SolarWinds' build environment - not the source code, the actual build servers - and modified binaries during compilation. For nine months, SolarWinds was basically a government-approved malware distribution service.

The SolarWinds breach affected over 18,000 organizations worldwide, including multiple U.S. government agencies.

The scary part? Everything looked legitimate. The malware was properly signed with SolarWinds' certificates, passed all security scans, and behaved like normal software until it was time to phone home. Even the Pentagon got infected through normal software updates.

What actually happened: Attackers got into the build environment and modified source code during compilation. Not the repo - the build server itself. The SUNBURST backdoor was inserted during the build process.

The attack showed how CI/CD systems are prime targets because they have broad access across infrastructure. CrowdStrike's analysis revealed the malware specifically targeted the build process.

Codecov (2021) - When Code Coverage Became Secret Harvesting

This one hit close to home because we were using Codecov too. Their bash uploader got modified to steal environment variables from every CI/CD run. Two months. That's how long every build leaked secrets before anyone noticed.

The Codecov incident report shows how supply chain attacks can stay hidden for months. CISA's cybersecurity advisory helped organizations assess potential exposure.

The worst part was watching the incident reports roll in. HashiCorp, Twilio, dozens of companies I recognized - all compromised through the same vector. We spent a weekend rotating every credential that might have touched a Codecov build.

What made it so effective was the perfect trust relationship. We're installing a tool specifically to analyze our code, giving it access to our entire build environment, and assuming it'll only do what it's supposed to do. Classic supply chain exploitation - abuse existing trust relationships.

The NPM Package That Ruined My Weekend (2021)

You know that feeling when you're debugging something for hours and then realize the problem isn't your code? That was me when the ua-parser-js package got compromised.

This package gets downloaded about a billion times a week - basically every JavaScript project uses it directly or indirectly. Someone stole the maintainer's NPM credentials and pushed versions with cryptocurrency miners. If you had automatic dependency updates enabled (and you should), congratulations, you just deployed malware to production.

I spent two days figuring out why our staging environment was suddenly slow as hell, then another day explaining to leadership why our deployment pipeline downloaded and ran mining software. Fun times.

The scary thing about this attack was how perfectly it exploited our automation. The NPM security advisory and detailed analysis from Snyk showed the scope. We built all these great systems for automatic updates, continuous deployment, fast iterations - and the attackers just rode that wave straight into production.

The Current Stuff That's Breaking My Brain

This new wave of attacks is getting smarter. The Ultralytics computer vision library got hit in December - same pattern but targeting AI/ML workflows specifically. They know those teams have expensive GPU clusters and less mature security practices.

The packages looked completely normal until you started training models, then they'd harvest credentials in the background. Clever timing - who's monitoring resource usage during training? That's expected to be high.

Why Most Security Solutions Miss the Point

Look, I get it. Security vendors need to sell something. But most of their solutions don't address the actual problem.

"We use HashiCorp Vault!" Cool, how do your build systems authenticate to Vault? Oh, with credentials stored in environment variables? Amazing.

"We scan our dependencies!" For what, known CVEs? These attacks don't show up in vulnerability databases. They're compromising legitimate packages and adding new malicious code.

"We Use Private Docker Registries"

Awesome, except your CI/CD system needs credentials to access those registries. And if those credentials leak (which they will), attackers have access to all your base images and can inject malware at the infrastructure level.

"Our Builds Run in Isolated Containers"

Sure, but what happens when the container has network access and cloud credentials? Container isolation doesn't help when the malware is designed to steal secrets and exfiltrate data during the build process.

The Real 2025 Threat Landscape

Supply chain attacks are exploding - Sonatype's report says they've increased over 700% in the last few years. 2025 has been particularly brutal for CI/CD security. ENISA's threat landscape report confirms the trend.

The scary part is attackers are getting smarter. Recent GitHub Actions compromises show they understand fork network vulnerabilities, how to abuse pull_request_target triggers, and how to evade audit logs by manipulating git tags. They're targeting specific CI/CD tools, container registries, and build infrastructure that lots of companies depend on.

GitHub Actions attacks keep coming. We've seen multiple Action compromises every few months. Attackers know that one compromised popular Action can give them access to thousands of repositories instantly. The dependency confusion attacks alone affected thousands of repositories before GitHub implemented better protections.

AI-powered attacks are analyzing your build patterns to find the optimal time and place to inject malicious code. They understand that your 3am deployment has less oversight than your Tuesday afternoon release. The Ultralytics attack specifically targeted AI/ML workflows because they knew those engineers have access to expensive GPU infrastructure.

Cloud-native environments introduced new attack vectors nobody thought about. Kubernetes service accounts, ECR permissions, serverless execution roles - every abstraction layer is another opportunity for privilege escalation. OIDC token hijacking is becoming the new credential theft.

What's Actually at Stake

When your CI/CD gets compromised:

  • Attackers get persistence: They don't need to maintain access to individual servers when they control the deployment pipeline
  • Lateral movement is trivial: CI/CD credentials often have broad access across your entire infrastructure
  • Detection is delayed: Malicious changes look like legitimate deployments in your logs
  • Recovery is expensive: You need to audit every deployment, rotate every credential, and rebuild trust with customers

Data breaches are getting more expensive - IBM's Cost of Data Breach Report says the average hit over $5 million in 2024. Ponemon Institute research shows supply chain breaches cost 19% more than average. That's just the direct costs, not the months of cleanup hell. Supply chain attacks are particularly devastating because of their wide blast radius across multiple organizations. The Codecov incident alone potentially exposed credentials for hundreds of companies simultaneously.

But the real cost isn't money. It's the months of recovery time, the customer churn, and the realization that your entire software delivery process can't be trusted.

Time for Some Honesty

Most companies are running CI/CD systems that were designed for convenience, not security. We prioritized developer productivity over security controls, and now we're paying for it.

The good news? The fixes aren't that complicated. You just need to stop treating CI/CD security as an afterthought and start treating it like the critical infrastructure it actually is.

Security Fixes That Actually Work in Production

Enough with the corporate security theater. Here's what you actually need to do to stop your CI/CD from getting pwned, based on fixing this shit in real environments.

Stop Leaking Secrets (This Is Job #1)

OIDC: The Only Authentication That Doesn't Suck

OIDC Authentication Flow

GitHub Security Logo

Storing AWS keys in GitHub secrets is like leaving your house key under the doormat. OIDC authentication lets your CI/CD talk directly to cloud providers without long-lived credentials. AWS documentation and Azure's guide provide implementation details.

## This actually works and I've used it in prod
- name: Configure AWS credentials  
  uses: aws-actions/configure-aws-credentials@v4
  with:
    role-to-assume: arn:aws:iam::123456789012:role/GitHubAction-AssumeRoleWithAction
    aws-region: us-east-1

Things that will ruin your day:

  • I spent 3 hours debugging OIDC because I used sts.aws.com instead of sts.amazonaws.com. Apparently that matters.
  • The trust policy syntax is repo:yourorg/yourrepo:ref:refs/heads/main - not repo:yourorg/yourrepo:main or any other logical format
  • Made the mistake of using wildcards in production once. Woke up to alerts about random repos assuming our AWS roles.

Takes a weekend to set up properly, but then you never have to rotate long-lived credentials again. Worth it. GitHub's security hardening guide and NIST's guidelines provide comprehensive setup instructions.

Environment Protection That Actually Stops Accidents

GitHub environments with protection rules are the only thing standing between your junior dev and accidentally deploying to production. Environment protection rules documentation and deployment branch policies explain the setup process.

## This config saved my ass multiple times
production:
  required_reviewers:
    - security-team
    - @senior-devs
  wait_timer: 5  # 5 minute cooldown
  deployment_branch_policy:
    protected_branches: true
    custom_branch_policies: false

Real talk: The 5-minute wait timer is crucial. It's saved us from panic deployments more times than I can count.

Fix Your Repository Security

Branch Protection: The Bare Minimum

If you're not doing this, you deserve to get hacked. Branch protection documentation and CODEOWNERS guide cover the basics:

## This goes in your .github/CODEOWNERS
.github/workflows/ @security-team @devops-team
Dockerfile* @security-team  
**/k8s/ @devops-team
package.json @security-team

Real talk: Our intern committed AWS credentials to a workflow file in March. CODEOWNERS caught it before it hit the main branch. Could've been a very expensive lesson.

The Dependency Pinning Hell

Every security guide says "pin your dependencies" but they don't tell you it's a massive pain in the ass. Here's how to do it without losing your mind:

## Pin to exact SHAs, not versions
- uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0
- uses: docker/build-push-action@2eb1c1961a95fc15694676618e422e8ba1d63825 # v4.1.1

Use Renovate to auto-update these pins. Trust me, doing it manually will drive you insane. Dependabot is GitHub's native alternative, and GitHub's security advisories help track vulnerabilities.

Container Security (Without the Bullshit)

Trivy Security Scanner Logo

Scanning That Actually Finds Real Problems

Most security scanners are useless because they flag every CVE regardless of exploitability. Trivy is different - it actually prioritizes based on what matters. Grype, Snyk, and Clair offer similar capabilities:

- name: Run Trivy scanner
  uses: aquasecurity/trivy-action@master
  with:
    image-ref: 'myapp:${{ github.sha }}'
    format: 'sarif'
    severity: 'CRITICAL,HIGH'
    ignore-unfixed: true

The ignore-unfixed flag is crucial - why fail builds on vulnerabilities that can't be patched yet?

Dockerfile Security That Developers Won't Hate

## Pin the base image SHA (this actually matters)
FROM node:18-alpine@sha256:435dcad253bb5b7f347ebc69c8cc52de7c912eb7241098b920f2fc2d7843183d

## Run as non-root (breaks some apps but worth it)
RUN addgroup -g 1001 -S nodejs && adduser -S nextjs -u 1001
USER nextjs

## This health check saved our asses during a silent failure
HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
  CMD curl -f localhost:8080/healthz || exit 1

This health check saved us during a memory leak incident in September. The app was slowly consuming more RAM, but the health check failed before it could take down the whole node. Sometimes simple fixes prevent big problems.

The Things Nobody Tells You About OIDC

AWS Trust Policies Are Picky As Hell

This trust policy is a nightmare to get working:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "Federated": "arn:aws:iam::123456789012:oidc-provider/token.actions.githubusercontent.com"
      },
      "Action": "sts:AssumeRole",
      "Condition": {
        "StringEquals": {
          "token.actions.githubusercontent.com:aud": "sts.amazonaws.com",
          "token.actions.githubusercontent.com:sub": "repo:yourorg/yourrepo:ref:refs/heads/main"
        }
      }
    }
  ]
}

Critical gotchas:

  • The sub field is case-sensitive
  • It won't work with pull requests unless you add separate conditions
  • The OIDC provider ARN must exist in your account first

Google Cloud Is Even Worse

GCP's workload identity setup is like solving a puzzle designed by someone who hates you:

## This command line from hell actually works
gcloud iam service-accounts add-iam-policy-binding \
  --role roles/iam.workloadIdentityUser \
  --member "principalSet://iam.googleapis.com/projects/PROJECT_NUMBER/locations/global/workloadIdentityPools/POOL_ID/attribute.repository/ORG/REPO" \
  SERVICE_ACCOUNT_EMAIL@PROJECT_ID.iam.gserviceaccount.com

Google's documentation for this is... not great. Took me way longer than it should have to get the syntax right.

Self-Hosted Runners: The Security Nightmare

Just Use Hosted Runners If You Can

Self-hosted runners are a security nightmare unless you know what you're doing. Every job runs on the same machine, so one compromised workflow can steal secrets from all the others.

If you must self-host:

  • Use ephemeral runners that get destroyed after each job
  • No persistent storage between jobs
  • Separate runner groups for different security zones
## This took forever to get working
apiVersion: actions.summerwind.dev/v1alpha1
kind: RunnerDeployment
metadata:
  name: secure-runner
spec:
  replicas: 5
  template:
    spec:
      ephemeral: true  # This is critical
      securityContext:
        runAsNonRoot: true
        runAsUser: 1001
      nodeSelector:
        dedicated: "github-runners"
      tolerations:
      - key: "github-runners"
        operator: "Equal"
        value: "true"
        effect: "NoSchedule"

The Nuclear Option: SLSA Build Provenance

SLSA generates cryptographic proof that your artifacts haven't been tampered with. It's overkill for most apps but required if you distribute software to others. Google's implementation guide, CNCF's software supply chain security guide, and OpenSSF best practices provide comprehensive coverage.

## This workflow is a pain to set up but worth it for releases
- name: Generate SLSA Provenance
  uses: slsa-framework/slsa-github-generator/.github/workflows/generator_generic_slsa3.yml@v1.7.0
  with:
    base64-subjects: "${{ steps.hash.outputs.hashes }}"

Warning: This adds 5-10 minutes to your build time and the documentation is terrible. But if you're serious about supply chain security, it's the gold standard. The Update Framework, in-toto, and Sigstore complement SLSA for complete software supply chain security.

Monitoring That Actually Helps

Most CI/CD monitoring focuses on build times and success rates. For security, you need to monitor:

  • Failed authentication attempts: Someone trying to brute force your runners
  • Unusual network connections: Builds shouldn't be talking to random IPs
  • Resource usage spikes: Cryptocurrency miners are resource-heavy
  • Secret access patterns: Who's accessing which secrets when

Set up alerts for anything weird. That 3am deployment to production? It should wake someone up.

The bottom line: CI/CD security isn't about implementing every possible control. It's about implementing the ones that actually prevent the attacks you're likely to face. Start with secrets management and work your way up.

Security Controls Reality Check (No Marketing BS)

Security Control

My Experience

Time Investment

Worth It?

Actual Cost

Skip If...

OIDC Authentication

Took a weekend to set up, haven't touched it since

Few hours of pain upfront

Absolutely

  • no more key rotation

Free

Never, seriously just do it

Branch Protection

Works exactly as advertised

Literally 5 minutes

Yeah, stops stupid mistakes

Free

You're solo and perfect

Secret Scanning

80% false alarms but catches real stuff

Weekly noise

I guess? Better than nothing

Maybe $50/month

Tiny projects

Container Signing

Broke our deployments twice

2-3 days of yak shaving

If you ship software, yes

Free (time expensive)

Internal tools only

SLSA Provenance

Docs written by sadists

Week+ of confusion

Compliance checkbox mostly

Free (suffering included)

Unless auditors demand it

Self-Hosted Runners

"Never again"

  • our platform team

Constant security issues

Just... don't

$500+/month minimum

Use hosted unless forced

Dependency Scanning

Cries wolf daily

Ongoing alert fatigue

Catches some real stuff

$50-500/month

Brand new projects

Questions Developers Actually Ask About CI/CD Security

Q

Why does my GitHub Action keep failing with "Unable to assume role"?

A

I spent way too many hours on this exact error last month.

Your trust policy is wrong

  • happens to literally everyone the first time.json{"StringEquals": {"token.actions.githubusercontent.com:sub": "repo:yourorg/yourrepo:ref:refs/heads/main"}}The format has to be exactly repo:org/repo:ref:refs/heads/branch.

I tried refs/head/main (missing the 's'), repo:org/repo:main (missing the ref part), and about five other variations before getting it right.Also make sure your audience is sts.amazonaws.com

  • not sts.aws.com like seems logical.
Q

How do I stop getting 500 secret scanning alerts for test data?

A

Create a .gitsecrets file to ignore false positives:# Ignore test secretstest-api-key-*mock-password-*example-*Or use GitHub's secret scanning custom patterns to reduce noise.For test files, rename them to .example or put them in a /fixtures/ directory that you exclude from scanning.

Q

Can someone actually steal secrets from my CI/CD logs?

A

Oh yeah, definitely. I've seen this more times than I want to admit:

  • Left debug logging on and accidentally echoed our database password in build logs
  • API calls that helpfully log the entire request when they 403 (including the API key)
  • Some npm package that dumps all environment variables when it starts up
  • Error messages that are way too helpful: "Authentication failed for user admin with password hunter2"

Pro tip: In GitHub Actions, use echo "::add-mask::$SECRET_VALUE" before any command that might touch that secret. Learned this one the hard way.

Q

Is it worth the hassle to pin all my Actions to SHA hashes?

A

Depends on your paranoia level. For internal apps, probably not. For software you distribute, definitely yes.

Use Renovate to auto-update the pins. Doing it manually will drive you insane:

## renovate: datasource=github-actions depName=actions/checkout
- uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608 # v4.1.0
Q

Why does my SAST scanner flag everything as high severity?

A

Because SAST tools are designed to be paranoid. They'd rather flag 1000 false positives than miss one real vulnerability.

Filter by exploitability, not just severity:

  • SQL injection in admin-only code? Probably fine
  • XSS in user input? Fix immediately
  • Hardcoded password in test file? Ignore

Focus on what attackers can actually exploit.

Q

Should I trust GitHub-hosted runners with production deployments?

A

Yes, they're more secure than most self-hosted setups. Each job runs in a fresh VM with no persistence between builds.

Self-hosted runners are harder to secure because:

  • Jobs share the same machine
  • You're responsible for patching the OS
  • Credentials can persist between builds
  • Network access to internal resources

Only self-host if you have compliance requirements or dedicated security staff.

Q

How do I know if a supply chain attack is happening right now?

A

Monitor for:

  • Unexpected network connections: Builds shouldn't talk to random IPs
  • Build time increases: Cryptocurrency miners are resource-heavy
  • New binary downloads: Check what your builds are fetching
  • Dependency changes: Set up alerts for new packages

Use Harden-Runner for GitHub Actions to monitor runtime behavior.

Q

What's the point of SLSA? It seems like overkill.

A

SLSA is mostly useful if you distribute software to others. It provides cryptographic proof your build wasn't tampered with.

For internal apps, it's probably overkill unless you have compliance requirements.

The provenance files are basically receipts saying "this artifact was built from this source code using this process." It's the software equivalent of a notarized document.

Q

My container scanner found 500 vulnerabilities. Now what?

A

90% of container vulnerabilities are in base images you can't control. Focus on:

  1. Fixable vulnerabilities: Only worry about things you can actually patch
  2. Exploitable paths: A vulnerability in a library you don't use isn't a risk
  3. Critical severity: Fix anything with CVSS 9.0+ immediately

Use ignore-unfixed: true in Trivy to filter out noise.

Q

Is dependency pinning worth the maintenance overhead?

A

For npm/yarn: Pin major versions, let patch versions float:

{
  "dependencies": {
    "express": "~4.18.0"  // Pin to 4.18.x, allow patches
  }
}

For Docker: Pin to specific SHAs for base images:

FROM node:18-alpine@sha256:435dcad253bb5b7f347ebc69c8cc52de7c912eb7241098b920f2fc2d7843183d

For GitHub Actions: Pin if you're paranoid, otherwise use version tags.

Q

How do I debug OIDC trust relationship issues?

A

CloudTrail is your friend here. Look for AssumeRoleWithWebIdentity events - they'll tell you exactly why AWS is being picky.

I've made all of these mistakes:

  • Typo in the repository name (case sensitive, obviously)
  • Used main instead of refs/heads/main in the branch condition
  • Forgot to create the OIDC provider in AWS first (classic)
  • Copy-pasted someone else's subject claim with their repo name

This debugging snippet saved me hours:

- name: Debug OIDC stuff
  run: |
    echo "Repository: $GITHUB_REPOSITORY"
    echo "Ref: $GITHUB_REF"
    echo "Subject should be: repo:$GITHUB_REPOSITORY:ref:$GITHUB_REF"

Compare that output to what's in your trust policy. Usually the problem jumps out at you.

Q

Can I just ignore security scanning in CI/CD?

A

If your app handles user data, financial information, or runs in production: no.

If it's an internal tool that processes non-sensitive data: maybe, but why take the risk?

The minimum viable security is:

  1. Secret scanning (prevents credential leaks)
  2. Dependency scanning (finds known vulnerabilities)
  3. Basic SAST (catches obvious coding mistakes)

Takes 30 minutes to set up, potentially saves you weeks of incident response.

CI/CD Security Resources That Don't Waste Your Time

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