Patch Tracking with AI agents

A Neotask agent tracks security patches across the stack by pulling open vulnerabilities from Snyk and Dependabot, cross-referencing them against what is actually deployed, and creating a prioritized Jira ticket for anything that needs a fix — with severity-based SLAs enforced automatically so a critical CVE gets escalated within hours while a low-severity dependency bump waits for the next normal sprint, instead of every finding landing in the same undifferentiated backlog.

How it works today vs. with Neotask

Vulnerability scanners are good at finding problems and bad at prioritizing them for a team that also has to ship product, which means the raw output from Snyk or Dependabot piles up into a backlog that looks equally alarming whether it contains a remote-code-execution CVE in a production-facing service or a minor version bump in a dev-only dependency. Engineering teams that see the same undifferentiated wall of findings every week eventually start ignoring the whole list, which is exactly the failure mode that lets a genuinely critical patch sit unaddressed for months next to a hundred low-priority ones. What is missing is not more scanning — it is the layer that decides which findings are actually urgent based on what is exposed and deployed, and enforces a different response timeline for each severity tier.

The agent flow

Pull vulnerability findings

The agent pulls new findings from Snyk for dependency and container scanning and Dependabot for repository-level alerts, rather than requiring someone to check both dashboards separately.

Integration: snyk

Cross-reference against deployed services

Each finding is checked against which services actually run the affected dependency in production, deprioritizing findings in code paths that are not deployed or not internet-facing.

Assign a priority tier

Severity, exploitability, and exposure combine into a priority tier — critical, high, normal — that determines the SLA clock rather than treating every CVE score the same.

Create the tracking ticket

A Jira ticket is created with the finding details, affected service, and priority tier pre-filled, assigned to the team that owns the affected service rather than a generic security backlog.

Integration: jira

Enforce the SLA clock

Critical findings trigger an escalation in Slack if not acknowledged within the tier's time window, and repeat escalations continue until the ticket is actioned.

Integration: slack

Verify the patch landed

Once a ticket is marked resolved, the agent re-checks the scanner output to confirm the vulnerability is actually gone from the next scan before closing the loop, catching fixes that did not fully deploy.

Report aggregate patch posture

A rolling report of open findings by tier, mean time to remediation, and overdue tickets is generated for security leadership, replacing a manual weekly status compilation.

Variations

Frequently asked questions

How is exposure determined for prioritization?

The agent checks which deployed services actually include the vulnerable dependency in their running build, so a vulnerability in an unused code path does not get the same urgency as one in a live production service.

What SLA applies to a critical finding?

Critical findings typically carry a same-day acknowledgment requirement with escalating Slack alerts until action is taken; the exact window is configurable per organization's risk tolerance.

Does this replace the scanners themselves?

No, it sits on top of Snyk and Dependabot output, adding prioritization, ticket creation, SLA enforcement, and verification the scanners themselves do not do.

How does it confirm a patch actually fixed the issue?

It re-checks the next scan cycle after a ticket is marked resolved and only closes the loop if the specific finding no longer appears, rather than trusting the ticket status alone.

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Plans

Free

$0/mo

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Individual

$50/mo

The full personal agent platform for one person.

Enterprise

$200/mo

Multiple workspaces and capacity for larger teams.

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