What this type of data looks like
Data for code security audit comes from source code repository commit records, third-party dependency component lists, static code scanning (SAST) tool outputs, and public vulnerability databases. Each audit task corresponds to a structured document collection. The collection includes four core file types: code audit reports, vulnerability proofs, repair suggestions, and retest records. Fields cover vulnerability severity, impact scope, dangerous function location results, data flow trace paths, repair steps, and more. Data is updated per project version or single audit task. No unified mandatory format exists, but core fields remain consistent. The setup adapts to security R&D and service provider teams of different sizes.
What constraints these characteristics impose on deployment and upgrade
Code security audit data sources are scattered. They include multiple heterogeneous sources such as code repositories, static scanning tools, and vulnerability databases. During deployment, access protocols and permission verification rules for different data sources must be adapted. The per-project-version update requirement means deployment must support scheduled configuration of incremental synchronization tasks. This avoids excessive cluster resource use from full data pulls. Documents include structured vulnerability reports and unstructured repair descriptions. Corresponding format parsing and storage rules must be configured. Errors may lead to high-risk vulnerabilities being launched. So alarm trigger thresholds and notification links must be configured during deployment. During upgrade, running audit tasks must stay uninterrupted.
How to set configurations
This configuration guide applies to code security audit scenario deployment and upgrade for FastGPT v4.17.0. The following lists recommended values and their basis for core configuration items:
| Configuration Item | Recommended Value | Basis for This Setting |
|---|---|---|
DB_MAX_LINK | 80–120 connections | Supports concurrent audit data read and write requests when connecting to multiple data sources such as code repositories and vulnerability databases. Prevents connection exhaustion. |
REDIS_URL | Cluster address with permission verification | Stores temporary cache for audit tasks and ticket session data. Ensures high availability and access security. |
STORAGE_S3_ENDPOINT | Endpoint address adapted to local storage | Stores large-volume files such as code audit reports and dependency lists. Matches access rules for internal storage services. |
FILE_TOKEN_KEY | 32-bit random string | Generates temporary access tokens for audit files. Restricts unauthorized access to sensitive audit data. |
ROOT_KEY | Encryption key only for internal operations | Configures system-level operation and maintenance permissions. Prevents unauthorized modification of audit tasks and knowledge base configurations. |
FE_DOMAIN | Domain name of the internal operation and maintenance workbench | Configures the front-end access entry for ticket Q&A. Connects to the internal IT ticket system. |
Three common errors
- Phenomenon: When deploying in the Alibaba Cloud DSW environment, the Docker service fails to start, and the FastGPT container cannot be started. Cause: The local storage mount path corresponding to
STORAGE_S3_ENDPOINTis not correctly configured, causing the container to fail to access the audit data storage directory. - Phenomenon: An error occurs when importing Excel-format audit data files, and the table content cannot be read. Cause: No valid key is configured for
FILE_TOKEN_KEY, causing file upload verification to fail and unable to obtain access permissions for imported data. - Phenomenon: After configuring English prompt rules, the model only outputs Chinese content. Cause: No language adaptation parameters for Q&A are specified in the knowledge base configuration, and the language training weights of the model are not aligned, causing the output language to not match the preset requirements.
How to verify correct configuration
- Run the built-in database connection test script to verify whether the
DB_MAX_LINKconfiguration takes effect. Check whether the active connection count of the connection pool falls within the set range of 80–120 connections. - Upload a test code audit report file to verify that the
STORAGE_S3_ENDPOINTstorage configuration works normally. The file can be stored normally and accessed via a temporary link. - Submit an internal test ticket to verify that the
FE_DOMAINconfiguration is correct. The ticket can be pushed to the Q&A system normally and generate responses that meet preset rules. - Generate a temporary file access token to verify that the
FILE_TOKEN_KEYconfiguration is valid. The token can access the uploaded audit files normally without permission errors.
The values provided here are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.