Clearly AI: Redefining Automated Software Security in the RSAC Innovation Sandbox

The **RSA Conference (RSAC) Innovation Sandbox** has a storied history of identifying the startups that will define the next decade of cybersecurity. This year, all eyes are on **Clearly AI**, an automated software security platform that has secured a coveted finalist spot. Clearly AI is tackling one of the most persistent problems in modern development: the "security bottleneck" in the **CI/CD pipeline**.

The Technical Edge: Context-Aware Vulnerability Scanning

Traditional **Static Application Security Testing (SAST)** and **Dynamic Application Security Testing (DAST)** tools are notorious for high false-positive rates. They often flag vulnerabilities that are theoretically possible but practically unreachable in the current application state. Clearly AI's platform differentiates itself through **Context-Aware Semantic Analysis**.

By building a **Control Flow Graph (CFG)** and a **Data Flow Graph (DFG)** of the entire application, Clearly AI can trace the path of untrusted input from a source to a sink. If the input is properly sanitized or if the vulnerable code path is never executed, the system automatically suppresses the alert. This reduction in "noise" allows security engineers to focus on the **top 5% of critical risks** that actually impact the production environment.

Autonomous Remediation: Beyond Identification

What truly sets Clearly AI apart is its **Autonomous Remediation** engine. Most security tools tell you what's wrong; Clearly AI suggests (and in some cases, automatically applies) the fix. Utilizing a fine-tuned **Large Language Model (LLM)** specifically trained on millions of secure coding patterns and CVE (Common Vulnerabilities and Exposures) patches, the system generates **Pull Requests (PRs)** that address the root cause of the vulnerability.

These PRs aren't just copy-pasted snippets. They are tailored to the project's existing coding style and dependencies. The platform also runs a suite of **regression tests** on the proposed fix to ensure that it doesn't break existing functionality. This "self-healing" capability is essential for organizations managing thousands of microservices where manual patching is no longer feasible.

Securing the AI Supply Chain

As organizations increasingly integrate AI models into their own software, Clearly AI is expanding its scope to include **AI Supply Chain Security**. This involves scanning for **prompt injection** vulnerabilities, insecure model configurations, and toxic training data. As the **OWASP Top 10 for LLMs** becomes the industry standard, Clearly AI is positioning itself as the primary enforcement mechanism for AI-first enterprises.

The platform's ability to analyze **vector database** queries and model weights for potential data leakage is a significant technical leap. By treating the AI model as just another component of the software stack, Clearly AI provides a **unified security posture** that covers both traditional code and non-deterministic AI components.

Conclusion: The Future of DevSecOps

Clearly AI's success at the RSAC Innovation Sandbox signals a broader industry shift toward **agentic security**. We are moving away from passive monitoring toward active, autonomous systems that can defend and repair themselves in real-time. For the modern CISO, platforms like Clearly AI offer the only viable path to managing the **exponential growth of the attack surface** in a cloud-native world.