Pensar provides a continuous adversarial testing platform that uses autonomous offensive AI agents to discover, prove, and patch vulnerabilities across an organization's entire attack surface. The platform integrates with CI/CD pipelines, maps applications and endpoints in real time, and ships validated exploits with working proof-of-concepts and auto-generated fixes. Every finding is retested to ensure all exploit paths are fully remediated.
Funding
Funding not disclosed
Founders
Product
Problem
AI-enabled threats are outpacing traditional security defenses, as attackers can now scale offensive operations horizontally by spending on tokens rather than human capital. Signature-based tools miss chained, multi-step attacks and business-logic flaws, while manual penetration testing is too infrequent and slow to keep pace with continuous code changes and an ever-expanding attack surface.
Solution
Pensar provides a continuous adversarial testing platform that deploys frontier offensive AI agents to autonomously map, discover, exploit, and patch vulnerabilities across an organization's entire attack surface. The platform unifies repositories, domains, applications, and infrastructure into a single evolving workspace, with agents that adversarially test every endpoint, API, service, and cloud resource. Each finding is rigorously verified with a working proof-of-concept, and the agent then auto-remediates the issue by opening a fix for review rather than handing over a ticket. The system continuously re-runs reconnaissance as code changes, maintains living threat models at the endpoint level, and retests after patches to ensure all exploit paths are closed.
Target Audience
Primary customers are security engineering teams, CISOs, and application security engineers at organizations that need continuous, AI-powered penetration testing and vulnerability remediation across their applications, APIs, and cloud infrastructure.
Features
- Autonomous offensive agents that discover and validate chained, multi-step attacks and business-logic flaws that signature-based tools miss
- Continuous reconnaissance that automatically re-maps the attack surface as code changes, with per-workspace cadence controls
- Living threat models that update in place at the endpoint level, reflecting the latest code and infrastructure changes
- Auto-remediation that ships a patch with every validated exploit, opening a fix for review instead of a ticket
- Working proof-of-concept and full agent trace included with every finding for triage of confirmed exploits
- Per-application access control with workspace tiers, enabling least-privilege security data access for developers and security engineers
- CI/CD integration for pentesting every deployment, with support for GitHub, GitLab, Bitbucket, and Azure DevOps