Red teams attack. Blue teams defend. Purple teams do both simultaneously, creating a feedback loop that improves both offense and defense. For software supply chain security, purple teaming is particularly valuable because supply chain attacks are complex, multi-stage operations that require both attacker knowledge and defender visibility to understand fully.
Traditional penetration tests check whether an attacker can breach your perimeter. Purple team exercises for supply chain security check whether an attacker can inject malicious code into your software pipeline -- and whether your team would notice before it reaches production.
Why Purple Teaming for Supply Chain
Supply chain attacks are different from traditional infrastructure attacks. They exploit trust relationships between developers, build systems, package registries, and deployment pipelines. A conventional penetration test might never touch these systems because they are not part of the traditional attack surface.
Purple teaming specifically tests whether your dependency monitoring catches a malicious package introduction, whether your CI/CD pipeline would execute a tampered build script, whether your code review process catches subtle backdoors, whether your signing and verification chain is end-to-end secure, and whether your SBOM and vulnerability scanning detect a compromised component.
The offensive team (red) provides realistic attack simulations. The defensive team (blue) attempts to detect and respond. Both teams work together (purple) to identify gaps and improve capabilities.
Exercise Structure
Phase 1: Threat intelligence briefing. Start with a shared understanding of real-world supply chain attacks. Brief both teams on recent incidents (SolarWinds, Codecov, event-stream, ua-parser-js) and the specific techniques used. This ensures the red team's simulations are realistic and the blue team knows what to look for.
Phase 2: Attack planning. The red team plans supply chain attack simulations within agreed-upon scope and safety boundaries. Attacks might include publishing a typosquatting package to an internal registry, modifying a CI/CD pipeline configuration to inject a build step, introducing a dependency with a known vulnerability pattern, creating a pull request with a subtle backdoor in lockfile changes, and simulating a compromised maintainer account.
Phase 3: Controlled execution. The red team executes attacks in the test environment while the blue team monitors using their normal tools and processes. The key is that both teams can see what is happening -- the red team sees whether their attack succeeds, and the blue team sees whether their detection fires.
Phase 4: Real-time feedback. After each attack, both teams discuss what happened. The red team explains the technique. The blue team explains what they saw (or did not see). Together, they identify detection gaps and improve monitoring rules.
Phase 5: Remediation and improvement. Based on the exercise findings, the team implements detection improvements, updates runbooks, and strengthens controls. These improvements are tested in the next exercise.
Supply Chain Attack Simulations
Dependency confusion test. The red team publishes a package to the internal registry with the same name as a public package, but with a higher version number. The test verifies whether the build system prefers the internal or public package, and whether monitoring detects the unexpected package source.
Build pipeline injection. The red team modifies a CI/CD configuration file (Jenkinsfile, .gitlab-ci.yml, GitHub Actions workflow) to add a step that exfiltrates environment variables to an external endpoint. The test verifies whether code review catches the change, whether pipeline monitoring detects unexpected network connections, and whether secrets are properly masked.
Lockfile manipulation. The red team creates a pull request that includes legitimate code changes plus subtle lockfile modifications that redirect one dependency to an alternative source. The test verifies whether code reviewers examine lockfile changes and whether automated lockfile validation tools catch the manipulation.
Compromised package simulation. The red team publishes a new version of an internal library with an added "phone home" capability. The test verifies whether dependency update processes include security review and whether runtime monitoring detects unexpected network connections from the application.
Metrics and Measurement
Track these metrics across exercises to measure improvement:
Detection coverage. What percentage of simulated attacks were detected by automated tools? By human review? Not detected at all?
Detection latency. How long from attack execution to first alert? To human acknowledgment? To containment action?
False negative analysis. For attacks that were not detected, why not? Missing monitoring coverage, alert fatigue, or process gaps?
Response effectiveness. When an attack was detected, was the response appropriate? Was the attack contained before it could achieve its objective?
Safety Boundaries
Purple team exercises for supply chain security must operate within strict safety boundaries. Never modify production build pipelines or registries. Use isolated test environments that mirror production. Agree in advance on which techniques are in scope. Have a kill switch to immediately stop any simulation. Ensure all simulated malicious packages are clearly labeled and cannot accidentally leak to production.
Building the Capability
Start with simple exercises and increase complexity over time. An initial exercise might focus on a single attack technique (typosquatting). Mature exercises can simulate multi-stage attacks that chain multiple techniques.
Involve developers, not just security professionals. Developers are the first line of defense against many supply chain attacks. Their participation in purple team exercises improves their ability to spot suspicious changes in code reviews and dependency updates.
How Safeguard.sh Helps
Safeguard.sh serves as a key blue team tool during purple team exercises. The platform's dependency monitoring, SBOM generation, and vulnerability scanning provide the detection capabilities that the blue team uses to identify simulated attacks. When exercises reveal detection gaps, Safeguard.sh's policy engine can be configured to close those gaps, creating a continuous improvement cycle between exercises and production monitoring.