Symbiotic Insights

A Carnegie Mellon study reveals that while AI agents successfully implement features 61% of the time, only 10.5% are actually secure—meaning 8 in 10 "working" patches are vulnerable. The research proves that functional tests and prompt engineering fail to catch deep security flaws like injection or timing attacks. The result: a critical need for independent guardrails to ensure "vibe coding" doesn't compromise production safety.

Symbiotic’s Deep Remediation replaces fragile patches with agentic workflows that reason across files to fix root causes. By verifying builds and providing developer micro-training, it scales 5x faster than manual remediation. The result: intelligent, contextualized security that fixes code without breaking developer flow.

AI assistants repeat security mistakes while developers improve. Symbiotic Security bridges this gap with Learned Guardrails, a memory system that converts past fixes into dynamic rules. This forces AI to evolve with the codebase, ensuring every remediation permanently improves future code quality.

At Symbiotic Security, we tested how well our AI engine can remediate insecure code through large-scale experiments. Using an LLM-as-a-Judge framework, we evaluated fixes across six dimensions of quality, from functionality to security completeness. Benchmarks on 190 projects in 7 languages with 5 judge models showed GPT-4.1 as the most consistent and highlighted the power of context engineering. The result: a trusted, measurable path to more reliable AI-powered remediation.

It’s not an overstatement to say that the Security Copilot redefines developer and code security. It does so by embedding education, context, and automation directly into the PR process.

Symbiotic's Security Copilot App has won the Blackbox.ai developer track hackathon at RAISE Summit 2025

The study “Security Degradation in Iterative AI Code Generation” made clear that more iteration on code using LLMs leads to more security vulnerabilities.

DevOps.com spotlighted the ongoing trade-off between speed and code quality, focusing largely on testing, performance, & maintainability, but not security.