A Secure Software Development Lifecycle integrates security into requirements, architecture, design, coding, testing, deployment, operation, and retirement rather than adding a penetration test immediately before release. The objective is to reduce defects early, control software supply-chain risk, protect build and deployment systems, and create evidence that released software meets defined security requirements. Security becomes a property of the engineering process rather than one team’s late-stage gate.
ISC2 CISSP treats software development security as a full lifecycle discipline, covering development methods, ecosystems, testing, acquired software, and secure coding rather than one pre-release scan. ISC2 CCSP adds cloud-application context, while ISACA CISM and ISACA CRISC connect development controls to governance, risk ownership, and program management. The ISC2 CISSP approach treats the SDLC as a complete lifecycle: security requirements inform design, engineering controls reduce defects, assurance verifies releases, operations monitor reality, and retirement removes leftover attack surface.
Define security requirements during planning
Requirements should cover authentication, authorization, data sensitivity, logging, privacy, availability, abuse prevention, regulatory obligations, and recovery. High-risk functionality such as payments, privileged administration, file upload, and external integrations deserves explicit security acceptance criteria. Security requirements should be testable rather than vague statements such as “use best practices.” SSDLC governance should define which security activities are mandatory by application risk. A public payment platform and an internal low-risk utility should not require identical review depth, but both need a defined baseline.
Security champions inside engineering teams can help translate central standards into day-to-day design and code decisions without making every question wait for a separate security team. Requirements should include abuse cases as well as normal use. Teams need to consider how attackers can misuse account recovery, search, export, file upload, invitations, or API functionality without exploiting a coding bug. Privacy requirements should be included during planning so systems minimize data and provide deletion, consent, or subject-right workflows before storage design becomes difficult to change. SSDLC programs should publish a minimum baseline and risk-tiered enhancements so engineering teams know which security activities are expected before work begins. Security stories and acceptance criteria should live in the same backlog as product work rather than a separate queue that is repeatedly deferred.
Product owners should understand when security defects are release blockers and when residual risk requires documented acceptance. SSDLC governance should also define secure exception handling. Teams will occasionally need to release with a known issue; the exception should document severity, exposure, compensating controls, owner, and remediation date. Repeated exceptions in the same area often reveal missing secure components or unrealistic standards and should trigger platform improvement. Product teams should know who can accept residual software risk and which vulnerabilities require escalation beyond the development manager.
Threat model before implementation
Map data flows, trust boundaries, entry points, privileged operations, and attacker goals while architecture is still easy to change. Threat modeling identifies design flaws that code scanning may never find. Threat models should identify trust boundaries, sensitive operations, external dependencies, and attacker goals early enough that architecture can change cheaply. Design review should include authentication, authorization, tenancy, session handling, cryptography, secret management, logging, rate limiting, and recovery.
Low-risk systems may use automated scanning and standard patterns, while high-risk systems add threat modeling, manual review, penetration testing, and stronger release approval. Architecture decision records can preserve why authentication, tenancy, encryption, or network choices were made and which threats they address. Security architecture reviews should be lightweight for approved patterns and deeper for new trust relationships, sensitive data, custom cryptography, or high-impact automation.
Use secure coding standards and reusable components
Teams should have language-specific guidance for input validation, output encoding, authentication, session handling, secrets, cryptography, error handling, and API security. Prefer reviewed framework features and libraries over custom security primitives. Secure coding standards should be specific to language and framework. Generic advice such as “validate input” needs concrete guidance on framework-safe query, encoding, serialization, and file-handling APIs. Developer training should focus on vulnerabilities relevant to the codebase rather than one annual generic course disconnected from real tools.
IDE plugins and linters can catch insecure patterns early, but they should supplement—not replace—code review and architecture thinking. Reusable secure components can reduce defect rate: centralized authentication libraries, secret-management clients, logging modules, and validated infrastructure templates. Shared components need owners and patch processes because one vulnerability can affect many applications simultaneously. Code-review checklists should focus on high-risk patterns rather than forcing reviewers to inspect every line for every possible vulnerability.
Automated static analysis can prioritize paths involving authentication, file handling, deserialization, cryptography, or command execution where defects may have greater impact. API security should include authentication, authorization, rate limiting, schema validation, and object-level access checks. Multi-tenant applications require explicit tenant isolation in queries, caches, object storage, logs, and background jobs. When one vulnerability class appears repeatedly, teams should improve frameworks, coding guidance, or shared libraries rather than fixing instances forever. Security reviews should become easier as products adopt approved frameworks, shared identity, secret management, logging, and infrastructure patterns. Reuse is a security control because it reduces one-off implementation error.
Protect source control and developer workflows
Require strong authentication, branch protection, reviewed changes, least-privilege repository access, and secure handling of secrets. Protect CI/CD configuration and build scripts because they determine what eventually ships. Source-control policy should protect branches, require review for sensitive paths, and prevent secrets from entering repositories. Secret scanning should run on commits and history where possible. Signed commits or protected release tags can improve provenance for high-assurance software, especially when build pipelines verify signatures.
Secrets scanning should include repositories, CI logs, issue trackers, build artifacts, and container layers because credentials can leak outside source code. Developers should use local test credentials that cannot access production data. Developer environments should be isolated from production data and credentials where possible. Local testing convenience should not grant broad access to customer records or production cloud roles.
Secure dependencies and the software supply chain
Use dependency pinning, software composition analysis, trusted repositories, SBOMs, signed artifacts, and monitored vulnerability feeds. The CVE model helps track known vulnerabilities, but malicious packages and compromised build pipelines may not begin with a CVE. Reduce unnecessary dependencies and review high-risk maintainers or packages. Dependencies should be pinned and inventoried. Automated updates are useful when paired with testing rather than blindly merging new versions into production.
Package provenance matters. Organizations can use internal mirrors, trusted registries, signature verification, and namespace controls to reduce typosquatting and dependency-confusion risk. SBOMs help identify vulnerable components after disclosure, but they need accurate generation and ownership to remain useful. Dependency update automation should use tests and staged rollout so security patches do not create uncontrolled reliability risk.
Use layered application security testing
SAST examines source or intermediate code, DAST tests running applications, IAST combines runtime context, and SCA analyzes dependencies. Manual review and penetration testing address logic and architecture that scanners miss. Testing depth should follow application risk. False positives need triage, but suppressions should be documented and revisited. Security-test results should be prioritized by exploitability and business impact. A huge backlog of untriaged scanner findings undermines trust in the program. Suppressions should include rationale, scope, owner, and expiry so false-positive decisions do not become permanent blind spots.
Dynamic testing should include authenticated application areas and APIs rather than only public landing pages. Fuzzing can reveal parser and protocol flaws that normal test cases miss, especially for file formats, network protocols, and native code. Penetration testing should target business logic and chained attack paths, not simply repeat scanner output. Security-testing environments should resemble production enough that findings are relevant while using synthetic or protected data according to policy.
Secure CI/CD and release artifacts
Build identities should be least-privileged and short-lived. Protect signing keys, artifact repositories, deployment roles, and production promotion gates. The DevOps lifecycle becomes a security boundary because automation can deploy vulnerable or malicious software at scale. Promote immutable artifacts rather than rebuilding separately in production. Secure defaults should be part of deployment. Disable debug modes, default credentials, unnecessary ports, permissive CORS, sample endpoints, and verbose error output. Externalize secrets into managed systems.
Infrastructure as code should define network, IAM, encryption, logging, and runtime security consistently. Secure configuration should be the normal path, not an optional hardening document. CI/CD runners should be isolated appropriately and should not receive long-lived administrator credentials. Use temporary workload identity and narrow deployment roles. Build environments should restrict outbound connectivity where practical because compromised dependencies can otherwise download payloads or exfiltrate build secrets.
Release artifacts should be immutable and signed. Production should deploy the artifact that passed testing rather than rebuilding from source separately. Code-signing keys and deployment credentials need stronger protection than ordinary developer tokens because compromise can distribute malicious software broadly. Infrastructure as code should pass security policy checks for IAM, network exposure, encryption, logging, and public storage before deployment. Deployment strategies such as canary, blue-green, or phased rollout can reduce the impact of security and reliability regressions.
CI pipelines should fail safely when security scanners are unavailable. Teams should define whether the release stops, uses cached evidence, or requires explicit approval rather than silently skipping checks. Container image policy can require approved base images, non-root execution, vulnerability thresholds, and signatures before deployment. Kubernetes admission policy can enforce workload security requirements at deployment time rather than relying on each application team to remember them. Serverless functions still need dependency, IAM, secret, and input validation even though the provider manages the operating system.
Build provenance should connect source commit, dependency lockfile, build environment, tests, and artifact digest so teams can reproduce and verify a released binary. Release approval should promote that exact artifact. Rebuilding later in a different environment weakens the evidence that security tests apply to what reached production. Runtime configuration should be managed as code or controlled configuration with change history. Secure code can become insecure through permissive feature flags, IAM, network, or debug settings.
SSDLC programs should maintain secure release criteria that combine unresolved vulnerability severity, architecture risk, test coverage, supply-chain evidence, and business context rather than relying on one scanner score. Keep SSDLC evidence linked to the exact release so auditors and incident responders can determine which tests, dependencies, approvals, and exceptions applied to the software that actually ran in production.
Monitor software in production
Runtime logs, WAF, EDR, application telemetry, vulnerability scanning, dependency alerts, and user-reported issues can reveal defects that escaped pre-release testing. Security teams should connect production incidents back to code versions and deployment history. Confirmed failures should become regression tests. Runtime protection should include secure configuration, WAF or API policy where relevant, dependency monitoring, EDR/container telemetry, and application logging. Production feedback should connect vulnerabilities and incidents back to source commit, artifact, deployment, and owner so remediation is traceable.
Security bugs found in production should become regression tests in the pipeline. The SSDLC improves when the same weakness cannot reappear silently. Runtime monitoring can detect exploitation, unusual behavior, or configuration drift that pre-release testing could not anticipate. Vulnerability disclosure processes should give external researchers a safe reporting path and internal teams a defined triage and remediation workflow. Security incidents should feed secure-coding training with real internal examples where appropriate, making lessons more relevant than generic lists. SSDLC maturity should be measured by escaped defects, remediation time, coverage of security activities, exception age, and repeat findings—not by the number of scanner tools purchased.
Security telemetry should identify application version so incidents and vulnerability reports can be scoped to affected releases quickly. Feedback loops should connect security operations, bug bounty, penetration testing, and customer reports into engineering priorities. Release metrics should track escaped security defects and repeated vulnerability classes so leaders can see whether the development process is improving rather than only whether individual bugs close quickly.
Retire software securely
End-of-life should remove DNS, credentials, certificates, cloud resources, data copies, repository secrets, pipelines, vendor access, and monitoring exceptions. End-of-life should remove endpoints, DNS, certificates, secrets, service accounts, third-party integrations, repositories, pipelines, data, and old firewall rules. Software retirement should include customer communication and data migration where services are externally used, not only infrastructure cleanup. Retirement checklists should verify that old API versions, mobile endpoints, test environments, and backward-compatibility paths are actually removed; forgotten legacy interfaces often retain weaker controls than the current product.