Aikido Security has officially introduced Altar-1, a cutting-edge artificial intelligence model designed to enhance cybersecurity operations directly within an organization’s infrastructure. This innovative model is aimed at allowing security teams to conduct vulnerability assessments and penetration testing without the need to transmit sensitive data to third-party cloud services.
Privacy-Focused Cybersecurity Solution
Altar-1 is specifically tailored for organizations with stringent privacy, regulatory, or operational requirements, such as financial institutions, healthcare providers, and industrial firms. By ensuring that both the AI model and the data remain under the control of the customer, Aikido Security positions Altar-1 as a solution that upholds data sovereignty and security intelligence.
The model integrates into the Aikido Machine, an autonomous penetration testing appliance designed to operate within client environments. This setup continuously identifies, exploits, and validates vulnerabilities across a network’s attack surface, utilizing Altar-1’s local AI capabilities to process sensitive data internally.
Technical Advancements and Optimization
Developed from the Z.AI GLM-5.3 model, Aikido Security has significantly reduced the storage size of Altar-1 from 1.51 TB to 328 GB. This was achieved through AWQ INT4 quantization and expert pruning, which removed less relevant components, optimizing the model for targeted security workloads.
The pruning process retained 168 out of 256 neural network components, known as experts, leading to a model that is 78.2% smaller than its full-precision predecessor. This reduction was guided by internal pentesting benchmarks, ensuring the model’s effectiveness in cybersecurity tasks without relying on customer data.
Performance and Future Developments
In internal benchmarks, Altar-1 demonstrated a recall rate of 60.4% across 32 known vulnerabilities, rediscovering 23 vulnerabilities in multiple test runs. Although the full-precision model achieved a slightly higher recall rate of 65.6%, Altar-1 retained 92% of its vulnerability coverage while significantly reducing infrastructure demands.
Available through Aikido’s Hugging Face organization, Altar-1 can be deployed on systems equipped with four NVIDIA H200 GPUs. Aikido Security plans to further optimize the model by exploring lower-bit formats and fine-tuning future iterations for various security tasks.
As cybersecurity threats continue to evolve, Altar-1 represents a significant step forward in providing organizations with robust, privacy-focused AI solutions to protect their critical data and systems.
