On March 12th, QiAnXin officially launched its first code security intelligent agent, Qcode Agents. As the first tangible achievement of its newly established AI company, this product focuses on the intelligent transformation of code security detection.

Unlike traditional tools, Qcode Agents emphasizes "multi-agent collaboration". Leveraging expert-level reasoning, multi-capability integration, and multi-scenario coverage, it deeply embeds security detection into the R&D process, significantly enhancing delivery efficiency and propelling domestic code security detection into a closed loop of "full-scenario intelligent agents".

QiAnXin stated that it has innovatively planned and developed an AI security product matrix, which will be gradually launched into the market in the future, providing industry customers with higher-level intelligent security solutions.

What is Qcode Agents? Cracking AI Illusions and Logical Blind Spots with Expert-Level Brains Since the beginning of the year, from Anthropic's launch of Claude Code Security to OpenAI's release of Open Code Security, they have triggered strong reactions in the industry, fully demonstrating the great potential of large models in code semantic understanding, security detection assistance, and other aspects.

However, in the era of AI, the core contradiction of application security has shifted from "rule matching speed" to "depth of logical understanding". Automated verification driven solely by large models or scanning for new elements of AI applications still falls short. The industry urgently needs a "brain" that can think like a senior expert, possesses profound practical experience, and has logical reasoning ability.

The birth of QiAnXin Qcode Agents is precisely to endow AI with this "expert-level brain". This product not only comprehensively covers the new elements of the AI supply chain, but also codifies more than ten years of front-line practical experience, allowing the intelligent agent to truly "understand" the business logic behind the code, thereby addressing AI "illusions" and logical blind spots from the root.

Ten years of practical experience have enabled a leap from "general model" to "domain expert". The reason why many AI security tools on the market are "inaccurate" lies in the lack of genuine offensive and defensive logic support. The "core intelligence" of Qcode Agents is trained from QiAnXin's unique vulnerability mining experience, which has been tested in real-world scenarios for over a decade, and high-value detection rules. This capability has been fully integrated into the platform's MCP tool invocation, professional skill execution, detection script orchestration, and standardized workflow, forming the cornerstone of Qcode Agents' precise judgment.

Process standardization: Solidify key steps such as scan initialization, vulnerability localization, and path generation into standard actions of the intelligent agent, ensuring that the detection process follows established rules.

Knowledge Resourceization: Structured reconstruction of tens of thousands of high-quality detection rules, establishing a dynamically callable resource library, enabling the intelligent agent to have a clear detection path and rigorous logical judgment.

This marks that Qcode Agents no longer rely on "blind guessing", but trace the source with precision like a senior security expert, fundamentally solving the pain points of traditional AI detection, which are "undirected and weak in logic".

Fully automated security closed loop: Qcode Agents has established a fully automated security closed loop encompassing the entire development lifecycle, from "perception-analysis-verification-fix-response", seamlessly integrating into every step of the developer's process, from coding, submission, and merging requests to continuous integration/deployment.

Perception: Monitor code changes in real-time and initiate analysis immediately.

Analysis: Utilize an expert-level detection engine to precisely identify risks.

Validation: Reproduce the vulnerability triggering path through dynamic simulation to eliminate false positives.