AI Security Testing for Space Systems
The only sustainable way to secure continuously evolving AI is with continuously evolving testing. Foinik uses genetic algorithms to evolve adversarial attacks against AI systems in satellites, ground stations, and space infrastructure.
Test AI decision-making in orbit planners, collision avoidance, and mission control systems for vulnerabilities before deployment.
Assess AI-powered ground station operations, telemetry analysis, and command validation systems against adversarial attacks.
Test AI communication protocols and autonomous routing decisions in satellite constellations for security weaknesses.
Attacks evolve like biological organisms—crossbreeding successful techniques and mutating to discover zero-day vulnerabilities.
Native support for CCSDS, TT&C, and satellite-specific APIs. Tests AI systems in their actual operational context.
Watch attack fitness improve across generations. See exactly how each vulnerability was discovered through evolution.
Initialize with known attack patterns from OWASP, research, and previous tests
Elite 10% survive unchanged. Top 40% breed. Bottom 50% eliminated
Successful attacks exchange techniques to create more sophisticated variants
30% get DNA changes—synonyms, unicode, authority tokens, context shifts
Each generation gets 20-30% better. Novel attacks emerge that were never programmed
Foinik is a research project exploring how evolutionary algorithms can discover vulnerabilities that traditional testing methods miss. Follow the development as we push the boundaries of AI security testing for space systems.