Averlon

Reduce your exposure window by automating vulnerability triage and remediation with agentic AI that delivers safe, context-aware code fixes to developers.

Averlon screenshot

About Averlon

Averlon is an agentic remediation operations platform designed to close the "exposure window"—the critical time between the discovery of a vulnerability and its resolution. While most security tools focus on generating massive backlogs of findings and severity scores, Averlon shifts the focus to active fixing. It leverages AI agents to determine what is materially exploitable in a specific environment and then delivers safe, verified fixes directly into developer tools. By addressing the root cause rather than just the symptoms, the platform aims to reduce the risk associated with unpatched vulnerabilities that attackers typically exploit within days. The platform works by analyzing attack chains across identity, network, and configuration settings to identify high-risk exposures. Its AI agents triage and prioritize issues by understanding the context of the environment, effectively eliminating "backlog noise" from non-exploitable findings. A core component is "Averlon Vibe Remediation," which generates code-level fixes and delivers them directly into Integrated Development Environments (IDEs), source control systems like GitHub, and Command Line Interfaces (CLIs). This ensures that remediation happens within the existing developer workflow, reducing friction between security and engineering teams. Averlon is primarily built for CISOs, cloud security engineers, and vulnerability management teams at enterprises handling complex cloud environments. It is particularly beneficial for organizations struggling with large CVE backlogs or those requiring rapid incident response for zero-day vulnerabilities. By automating the manual triage load, security analysts can shift their focus from repetitive ticket management to strategic security outcomes. The platform is also highly relevant for DevOps teams who need to prevent new exposures from entering production through pre-merge analysis using tools like Averlon Precog. What sets Averlon apart is its transition from passive prioritization to active remediation. Unlike traditional vulnerability scanners that leave the "how-to-fix" part to the user, Averlon's agentic AI generates actual code changes while considering potential breaking changes. Its ability to map exactly how an attacker might compromise an environment provides a holistic view of risk that goes beyond simple CVSS scores. This proactive approach, combined with its direct integration into development pipelines, allows organizations to increase remediation velocity by up to 100x, moving from a 200-day average to minutes.

Pros & cons

Pros

  • Reduces the time to remediate critical exposures by up to 90%.
  • Integrates directly into developer workflows including IDEs, GitHub, and CLI.
  • Significantly lowers manual triage load by reducing false positives by 95%.
  • Identifies complex attack chains across identity, network, and configuration layers.
  • Prevents production backlogs by analyzing code and infrastructure changes pre-merge.

Cons

  • Pricing information is not publicly available and requires a custom demo request.
  • Requires deep integration into source control and developer environments to be fully effective.
  • The focus on enterprise-scale cloud environments may be overly complex for very small teams.
  • AI-generated fixes still require developer oversight to ensure they align with specific business logic.

Use cases

  • Vulnerability Management teams can shrink their CVE backlogs by delivering automated, safe fixes directly to developer workflows.
  • Cloud Security Engineers can map and break complex attack chains across identity and network layers before exploitation occurs.
  • CISOs can gain a holistic view of material exposure and present measurable risk reduction metrics to their company board.
  • DevOps Engineers can use the Precog feature to catch security flaws in infrastructure-as-code before they are merged into production.
  • Security Operations Centers can use agentic AI to automate the triage of zero-day vulnerabilities, saving significant manual engineering hours.

Features

  • attack chain analysis
  • environmental risk reasoning
  • exposure window reduction
  • automated triage
  • ide and github integration
  • averlon precog pre-merge
  • context-aware code fixes
  • agentic ai remediation

Pricing

Enterprise

Price varies

  • Agentic AI triage
  • Safe code fixes in IDE
  • Attack chain analysis
  • Averlon Precog pre-merge
  • Vulnerability prioritization
  • Context-aware remediation
  • Source control integration
  • Environmental risk reasoning

FAQs

How does Averlon prioritize vulnerabilities?

Averlon uses environmental reasoning to determine what is materially exploitable rather than relying solely on CVSS scores. It analyzes attack chains across identity and network configurations to surface the exposures attackers are most likely to exploit.

Where are the AI-generated fixes delivered?

Fixes are delivered directly into the developer's existing workspace, including IDEs, GitHub, and CLI tools. This context-aware remediation ensures that developers don't have to leave their primary tools to resolve security issues.

What is Averlon Precog?

Averlon Precog is a pre-merge analysis tool that evaluates infrastructure and code updates before they are merged. This proactive feature prevents new exposures from entering the production environment and becoming part of the security backlog.

Can Averlon help with zero-day vulnerability response?

Yes, the platform is built to accelerate incident response for critical issues like 0-day vulnerabilities. For example, it has been used to save hundreds of engineering hours during responses to high-profile issues like CVE-2023-4863.

How much does Averlon reduce false positives?

By using AI to reason about the specific environment and actual exploitability, the platform can reduce false positives by up to 95%. This helps security teams focus on defensible remediation decisions rather than manual triage of noise.

Open roles

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Senior Software Engineer

Benefits:

  • Medical insurance

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