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

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.
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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.
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.
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.
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.
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.
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