In enterprise security, the gap between knowing about a vulnerability and actually closing it is where breaches happen. The global average cost of a data breach reached $4.88 million in 2024, according to IBM’s Cost of a Data Breach Report and attackers increasingly weaponize known, internet-exposed flaws faster than many teams can remediate them. In many security organizations, the people best equipped to hunt threats spend their days as ticket clerks, manually creating, updating and closing vulnerability records one by one. Stale tickets pile up, fixed issues stay marked open and real risk hides inside an unmanageable backlog.
For one leading US communications provider, that manual lifecycle had become both a security liability and a drain on scarce engineering talent, so it turned to Persistent to automate it.
The client is a leading US-based cloud communications provider, delivering integrated voice, contact center and collaboration services to enterprises worldwide. It operates in a market where customers and partners evaluate vendors on demonstrable remediation governance, making rapid and provable vulnerability closure essential to customer trust and enterprise readiness.
A Stale Ticket Backlog That Masked Real Risk
For the client, vulnerability management had quietly turned into a security and operational liability. Its Jira environment held roughly 1,000 vulnerability tickets, many of them stale for weeks or months and some left open long after the underlying code was patched. Creating, updating and auditing these tickets one by one consumed hours that skilled security engineers could have spent on threat detection and prevention, while manual entry introduced priority and ownership errors. Tickets that still showed open for already-fixed issues created false risk visibility, weakened audit evidence and let genuinely exploitable, internet-facing flaws compete for attention inside a growing backlog. A rigid one-vulnerability-to-many-hosts model added approval bottlenecks and ownership ambiguity that slowed remediation further.
Automated Vulnerability Ticket Lifecycle from Creation to Closure
Persistent designed and implemented an end-to-end Jira vulnerability ticket lifecycle automation that integrates security scanner data with enterprise workflow governance. Bridging security, DevOps and ITSM expertise, Persistent built automation that respects the client’s existing Jira workflows, ownership models and reporting requirements rather than forcing new process friction. The solution delivered five capabilities:
- Automated Ticket Creation: A Python-based Jira API automation creates vulnerability tickets enriched with full security context, including security rationale, proof, severity, affected assets, scope of change and remediation guidance, replacing manual data entry.
- SLA-Aging Escalation: A Jira query identifies tickets older than 30 days with no progress and automatically adds tailored comments, tags the responsible managers and adds them as watchers.
- Validated Closure Control: Once a patch is applied and the scanner confirms a clean result, the automation transitions tickets from Security Review to Resolved, so closure happens only on validated remediation.
- Bulk Field Maintenance: The same automation performs bulk updates to labels, sprint details and other ticket fields across large volumes of tickets at once.
- Extensible Security Chatbot: Building on the API-first foundation, a chatbot integrates across the vulnerability scanner, EDR, phishing email validation and penetration port scanning to extend the platform to adjacent security workflows.
50 Hours Reclaimed Monthly and Faster Risk Reduction
With Persistent, the client was able to:
- Reclaim roughly 50 hours of security engineering time each month, converting administrative effort into capacity for threat detection and prevention.
- Shrink mean time to remediate by reducing the window, a new vulnerability sits unseen from days to seconds, cutting attack surface exposure.
- Create 100 tickets in under 5 minutes, a task that previously took 3 to 4 hours of manual work and reduce per-ticket creation time from about 10 minutes to under 5 minutes.
- Improve internal SLA compliance by 20% to 30% through automated comments and escalations as deadlines approach.
- Eliminate stale and already-fixed open tickets, with auto-resolution closing records as soon as a scan validates the fix to produce more accurate risk reporting.
- Achieve 100% data parity between the security scanner and the Jira ticket, removing the 10% to 15% error rate that came with manual entry.
- Prevent ticket flooding by grouping the same vulnerability found across environments, protecting engineering focus and feature delivery timelines.
Engineering Security Automation That Teams Actually Adopt
Persistent led the design and implementation of an end-to-end Jira vulnerability ticket lifecycle automation that integrates security scanner data with enterprise workflow governance. Its contribution spanned four areas:
- Automation engineering: Python-based Jira API automation for ticket creation, field updates, watcher escalation, comment tagging and closure transitions.
- Data fidelity design: A standardized ticket schema ensuring full parity between scanner findings and Jira fields, covering severity, proof, rationale, remediation and affected assets.
- Operational governance: SLA-aging logic and escalation patterns aligned with security risk and ownership accountability.
- Lifecycle hygiene: Automated state transitions from Security Review to Resolved based on validated scan outcomes.
What set Persistent apart
- Security-to-workflow engineering expertise: Persistent’s deep experience bridging Security, DevOps and ITSM workflowsenabled automation that is technically reliable and operationally adopted.
- Framework-driven prioritization: Automation followed risk-based criteria such as exploitable, internet-facing, zero-day and CISA-alerted issues to prevent ticket flooding and focus engineering on validated high-impact risks.
- Data parity and governance by design: Every created ticket includes the complete security context, including CVSS severity, proof, rationale, affected assets and remediation guidance, reducing downstream confusion and rework.
- Lifecycle closure as a control: Rather than treating closure as a manual task, Persistent implemented closure automation as a governance control, so tickets close only when scanning validates remediation, improving audit defensibility.
- Scalable extensibility: The same API-first foundation supports future expansion, including chatbot integration across vulnerability tools, EDR, phishing validation and port scanning, reducing the time to implement new security workflows.
From Ticket Administration to Engineering Outcomes
“Persistent helped us transform vulnerability management from a manual, error-prone process into an automated lifecycle with accurate data and measurable SLA governance. Our security team now focuses on engineering outcomes rather than ticket administration.”
Security Operations Leadership, the client
Scaling a Proven Automation Foundation
Persistent turned a manual, error-prone vulnerability ticketing process into an automated lifecycle that creates, escalates and closes tickets with full data fidelity and measurable SLA governance. The result is reclaimed engineering capacity, faster risk reduction and audit-ready remediation evidence, built on an API-first foundation designed to extend well beyond its first use case.
Building on that foundation, the next phase focuses on:
- Extending the integrated chatbot across the full security toolchain, spanning the vulnerability scanner, EDR, phishing email validation and penetration port scanning, to give analysts a single conversational entry point.
- Applying the same automation patterns to adjacent security workflows, so new use cases reuse proven schemas and escalation logic rather than starting from scratch.
- Deepening SLA and governance reporting to give security leadership real-time visibility into remediation posture and audit readiness.
