DeepFactor provides a platform that integrates software composition analysis, container scans, and runtime security to identify and prioritize vulnerabilities based on actual application behavior. This approach enables developers to enhance code security while maintaining productivity, effectively reducing false positives and alert fatigue in the application security process.
Funding
$15M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional application security approaches often generate numerous alerts, many of which are false positives or low-risk, leading to alert fatigue and inefficient use of developer and security team resources. Prioritizing vulnerabilities based solely on static analysis without considering runtime behavior can result in wasted effort on issues that pose little real-world threat.
Solution
Deepfactor provides an application security platform that integrates software composition analysis (SCA), container scanning, and runtime security to identify and prioritize vulnerabilities based on actual application behavior. By correlating static scan data with runtime analysis, Deepfactor reduces false positives and focuses remediation efforts on vulnerabilities that represent a true risk. The platform generates software bill of materials (SBOMs) and detects insecure file, network, and memory behavior in running containers. This integrated approach enables DevSecOps teams to shift security left, proactively address supply chain risks, and achieve compliance with security frameworks.
Target Audience
The primary users are DevSecOps teams, security engineers, and application developers responsible for securing cloud-native applications and managing software supply chain risks.
Features
- Software Composition Analysis (SCA) for identifying vulnerabilities and license risks in open-source dependencies
- Container scanning to detect vulnerabilities in container images
- Runtime security analysis to detect insecure application behavior, such as privilege escalation and remote code execution
- Correlation of static SCA findings with runtime usage behavior to prioritize vulnerabilities based on reachability and exploitability
- Generation of SBOMs in industry-standard formats (SPDX, CycloneDX)
- Integration with CI/CD pipelines to gate builds based on security policies
- Integration with Jira, Slack, and other tools for streamlined security reporting and collaboration
- REST APIs and HTTPS webhooks for integration with security dashboards and workflows