SentinelForge - Autonomous AI Security Team

Problem & Solution Statement Modern software increasingly relies on AI-assisted development, allowing developers to generate large amounts of code quickly. However, faster development can also introduce security vulnerabilities, logical bugs, inadequate testing, and insecure implementation patterns. Existing security tools often operate independently, leaving developers to manually correlate findings, reproduce issues, implement fixes, and verify that fixes did not introduce regressions. SentinelForge addresses this problem by functioning as an autonomous AI security engineering team rather than a conventional code scanner. A central AI Orchestrator analyzes a software repository and delegates tasks to specialized agents: Security Auditor Agent identifies vulnerabilities using AI reasoning combined with static analysis, dependency scanning, secret detection, and security rules. Testing Agent understands application behavior and automatically generates unit, API, boundary, regression, and security-oriented tests. Bug Hunter Agent searches for functional and business-logic flaws that may not appear as conventional security vulnerabilities. Fix Agent analyzes validated findings and generates targeted code patches. The agents' findings are then combined by a Finding Correlator, which removes duplicates, combines evidence, assigns severity and confidence, and creates a unified security assessment. SentinelForge then executes a critical verification loop: Detect → Test/Exploit → Analyze → Fix → Retest → Rescan → Verify Proposed fixes are applied inside an isolated Docker sandbox. The system reruns the original tests, newly generated tests, and security analysis before marking a vulnerability as resolved. If verification fails, the issue is returned to the repair workflow rather than being falsely marked as fixed. The target users are software developers, security engineers, development teams, startups, and organizations adopting AI-assisted software development. Users can provide a repository through the web interface and receive an interactive security dashboard containing vulnerabilities, bugs, generated tests, agent activity, remediation patches, verification results, and an overall security report. What makes SentinelForge unique is its multi-agent collaboration and evidence-backed verification loop. Instead of simply telling developers that code may be vulnerable, it attempts to reproduce the problem, proposes a fix, and independently validates whether the fix actually works.