Code & Integration Security

Problems with Code & Integration

Source code security increasingly depends on the ability to inspect integrations and legacy systems that often serve as weak links in enterprise environments. Many organisations rely on outdated software, third-party APIs, and interconnected vendor platforms that were not originally designed with modern cyber threats in mind.

Core Source Code Security

Securing integrations and protecting legacy code is less about patch everything which is mostly impossible and more about wrapping these systems in modern security controls, continuous AI-driven monitoring, and strong recovery planning.

Inspection of Integrations

  • Scan all third-party APIs for weak or outdated authentication methods (e.g., basic auth instead of OAuth2).
  • Monitor for excessive permissions and over-privileged tokens that could be abused if compromised.
  • Evaluate third-party software suppliers for patching cadence, vulnerability disclosure, and compliance (e.g., ISO 27001, SOC 2).
  • Continuously monitor CTI (Cyber Threat Intelligence) feeds for known vulnerabilities in integrated vendor products.
  • Maintain a Software Bill of Materials (SBOM) that documents all dependencies, libraries, and external components used.

Inspection of Legacy Code & Systems

  • Inspect static code for insecure coding practices, hardcoded secrets, or deprecated functions.
  • Dynamic testing in sandboxes to simulate malware or exploit behaviour in legacy apps.
  • Cross-reference code with vulnerability databases (e.g., CVE, CISA KEV catalog) to identify risks.
  • Automatically generate patching priorities based on exploit likelihood and business impact.
  • Review legacy systems for insecure defaults (e.g., SMBv1, NTLM authentication, outdated TLS versions).

Continuous Monitoring & Threat Simulation

  • Generate predictive models of how attackers could chain vulnerabilities in integrations and legacy apps.
  • Run automated red-team simulations (e.g., ransomware injection via a third-party API) to test defences.
  • AI-driven dashboards can generate executive-level summaries of risks in plain language while providing engineers with technical remediation paths.