Multi-Agent Based Automation of Developer Security Bot Notifications and Triage

Manual vulnerability notification creates friction, delays remediation, and obscures context. This workflow automates the handshake by deploying specialized agents within Slack or Microsoft Teams. These bots ingest findings from SCA, SAST, and DAST tools like Snyk or Checkmarx, then initiate conversations with the responsible developer or squad. The system correlates the vulnerability with code ownership from GitHub or GitLab, assesses exploitability using threat intelligence, and presents a structured summary with suggested next steps, eliminating the need for security teams to manually create and assign Jira tickets.

Implementation requires integrating the bot framework with your CI/CD pipeline and identity provider for accurate routing. The orchestrator, built with LangGraph or a similar framework, manages state, handles developer interactions, and enforces SLAs—escalating to a system of record like Jira if a response isn't received. Controls include configurable approval gates for critical issues, audit logs of all bot interactions, and the ability for security teams to monitor the triage queue. The result is a measurable reduction in mean time to acknowledge (MTTA) and a shift of repetitive triage labor from security analysts to an automated, conversational layer.

This workflow automates the critical bottleneck of routing vulnerability alerts from scanners (SAST, SCA, DAST) to the correct developer and gathering initial context. It replaces manual Jira ticket creation, email threads, and Slack pings with a structured, conversational interface. The operational upside comes from compressing the 'alert-to-acknowledgment' cycle from hours or days to minutes, directly improving mean time to remediate (MTTR) and freeing security engineers from triage toil. Implementation integrates with security tools (Snyk, Checkmarx), identity providers, and CI/CD systems via APIs.

The architecture is built on an orchestrator agent that manages state and logic, delegating to specialized agents for notification, context retrieval, and ticketing. Controls include configurable SLAs for developer response before automatic escalation, approval gates for high-severity auto-fixes, and full observability into bot interactions. Implementation uses frameworks like LangGraph for stateful workflows, integrates with enterprise SSO for identity, and requires careful design of conversation flows to handle exceptions, ambiguous ownership, and false positives without frustrating development teams.

Phase one delivers immediate ROI by automating the alert-to-notification loop. We integrate your SCA/SAST tools (Snyk, Checkmarx) with a lightweight orchestrator that parses new findings, enriches them with exploitability data, and posts structured alerts to designated Slack channels. This eliminates manual ticket creation and email forwarding, cutting initial notification latency from hours to seconds. The bot includes simple interactive buttons for developers to acknowledge or request more context, establishing the foundational conversational interface.

Phase two introduces intelligent triage and SLA enforcement. The orchestrator uses a routing agent to map vulnerabilities to code owners via git history or service catalogs, ensuring alerts reach the right squad. A separate escalation agent monitors response times against configured SLAs; if a critical finding is unacknowledged, it automatically pings team leads or creates high-priority Jira tickets. This phase builds in approval gates for exception handling and integrates observability (Datadog, OpenTelemetry) to track bot performance and remediation velocity, providing the control layer needed for enterprise rollout.

This workflow targets the critical bottleneck where security alerts languish in ticketing systems, disconnected from developer workflows. By deploying conversational AI agents within Slack or Microsoft Teams, vulnerabilities from SCA, SAST, and CSPM tools are immediately contextualized and routed to the correct code owner. The operational upside is a 60-80% reduction in initial triage time, directly shrinking the mean time to acknowledge (MTTA) and remediate (MTTR) critical risks, while keeping developers in their primary collaboration environment.

Implementation requires integrating the bot agent with security tools like Snyk, Checkmarx, or Wiz via their APIs, and with Git systems for ownership mapping. The orchestrator, built on frameworks like LangGraph, manages state, enforces SLAs, and logs all interactions for audit. Controls include mandatory human acknowledgment for critical issues, configurable escalation paths based on severity and time, and immutable logs of all bot-developer interactions fed into the SIEM for compliance reporting.