

Month: 2025-12. Focused on delivering core vulnerability-detection improvements for Apache Tomcat and CVE-2024-50379 in Ostorlab/agent_asteroid, with targeted refactors, enhanced tests, and clearer signals to accelerate remediation and reduce risk.
Month: 2025-12. Focused on delivering core vulnerability-detection improvements for Apache Tomcat and CVE-2024-50379 in Ostorlab/agent_asteroid, with targeted refactors, enhanced tests, and clearer signals to accelerate remediation and reduce risk.
September 2025 highlights for Ostorlab/oxo: Implemented explicit vulnerability risk data and exposed it via the report_vulnerability API, and stabilized the test suite across Python 3.9 and 3.11, delivering clearer risk visibility and more reliable releases.
September 2025 highlights for Ostorlab/oxo: Implemented explicit vulnerability risk data and exposed it via the report_vulnerability API, and stabilized the test suite across Python 3.9 and 3.11, delivering clearer risk visibility and more reliable releases.
July 2025 — Ostorlab/agent_asteroid delivered targeted CVE scanning with custom CVE lists, enabling precise vulnerability assessment and faster triage. Implemented YAML config CVE_list and CLI filtering, with agent-level support for selecting exploits by CVE IDs and metadata integration. The feature rollout also included bug fixes to YAML field naming and consistent CVE_ID propagation, ensuring reliability and auditability. Changes were implemented across multiple commits to asteroid_agent.py, establishing a cohesive CVE-driven workflow. Result: reduced scan noise, shorter remediation cycles, and improved automation readiness for compliance reporting. Technologies: Python, YAML, CLI parsing, and metadata handling. Business value: higher accuracy, performance, and traceability of vulnerability scans.
July 2025 — Ostorlab/agent_asteroid delivered targeted CVE scanning with custom CVE lists, enabling precise vulnerability assessment and faster triage. Implemented YAML config CVE_list and CLI filtering, with agent-level support for selecting exploits by CVE IDs and metadata integration. The feature rollout also included bug fixes to YAML field naming and consistent CVE_ID propagation, ensuring reliability and auditability. Changes were implemented across multiple commits to asteroid_agent.py, establishing a cohesive CVE-driven workflow. Result: reduced scan noise, shorter remediation cycles, and improved automation readiness for compliance reporting. Technologies: Python, YAML, CLI parsing, and metadata handling. Business value: higher accuracy, performance, and traceability of vulnerability scans.
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