Image scanning checks what is present before deployment, while runtime threat detection watches what the container actually does once it is running. Scanning can find known vulnerabilities and missing dependencies, but it cannot observe live exploitation, escape attempts, or unexpected network behaviour. Mature programmes need both, because they answer different questions about risk.
Why This Matters for Security Teams
Image scanning and runtime threat detection answer different operational questions, and treating them as interchangeable creates blind spots. Scanning is a pre-deployment control: it identifies known packages, misconfigurations, and vulnerable layers before a container is promoted. runtime detection is an in-execution control: it observes process, file, syscall, and network behaviour to catch exploitation, lateral movement, and policy violations that never appear in an image manifest.
That difference matters because modern container risk is not limited to what was shipped. Attackers increasingly target exposed secrets, weak identities, and live workloads after deployment, which is why NHI governance has become central to container security. NHIMG’s Ultimate Guide to NHIs — Why NHI Security Matters Now shows how common compromised non-human identities remain, and CISA’s cyber threat advisories repeatedly emphasise that active exploitation often follows quickly after exposure.
In practice, many security teams encounter runtime compromise only after a clean scan has already been used as evidence that the environment was safe.
How It Works in Practice
Image scanning is most useful as a build-time and admission-time gate. It inspects container images for vulnerable libraries, outdated base images, embedded secrets, and policy violations before deployment. That makes it good at preventing known bad artefacts from entering the cluster, and it aligns well with supply-chain controls described in the Top 10 NHI Issues and the NHI Lifecycle Management Guide, where identity and secret hygiene are treated as lifecycle problems, not one-time checks.
Runtime threat detection, by contrast, watches the workload after it starts. It can flag shell spawning in a supposedly non-interactive service, unexpected outbound connections, tampering with mounted files, privilege escalation attempts, or anomalous access to cloud metadata. That is especially important when an image is clean but the workload receives a stolen token, a compromised API key, or a malicious command at execution time. For that reason, runtime controls should be paired with workload identity, least privilege, and short-lived secrets rather than relying on static image trust alone.
- Use scanning to block known vulnerabilities and detect embedded secrets before release.
- Use runtime detection to observe actual behaviour, including process, syscall, and network anomalies.
- Correlate runtime alerts with identity and secret telemetry so compromise can be traced to the active workload.
Current guidance suggests the strongest model is layered: shift-left scanning for prevention, plus runtime detection for verification and containment. These controls tend to break down in ephemeral auto-scaling environments when alert routing is delayed, because workloads can terminate before forensic signals are captured.
Common Variations and Edge Cases
Tighter runtime controls often increase operational overhead, requiring organisations to balance detection depth against performance, noise, and tuning cost. That tradeoff becomes sharper in environments with fast CI/CD, short-lived jobs, or serverless-style containers, where aggressive policy checks can slow releases or overwhelm responders.
There is no universal standard for exactly how much runtime visibility is enough. Best practice is evolving toward behaviour-based detection backed by policy-as-code, rather than static allowlists alone. The Anthropic report on AI-orchestrated cyber espionage is a useful reminder that automated workloads can chain actions quickly once they gain execution. That is why scanning cannot be the final assurance signal.
For teams adopting cloud-native controls, the practical answer is usually both. Scan every image, but assume runtime is where true risk emerges, especially when secrets are present in code paths, service accounts are over-privileged, or third-party integrations expand the blast radius. NHIMG’s 52 NHI breaches Report reinforces that identity abuse and exposed credentials often become operational incidents only after deployment. In container estates with heavy sidecars, legacy daemons, or unmanaged root processes, runtime detection can also generate false positives unless baselined carefully.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 and CSA MAESTRO address the attack and risk surface, while NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-03 | Covers secret rotation and exposure risks that scanning may miss once a workload is live. |
| NIST CSF 2.0 | DE.CM-1 | Runtime threat detection is continuous monitoring of containers and workload behaviour. |
| CSA MAESTRO | Helps align container and AI workload protections across build-time and runtime stages. |
Pair image scanning with runtime secret revocation and enforce short TTLs for any credential used by the workload.
