SAAI
SAAI is an enterprise-grade security tool designed to scan and protect AI models from emerging threats such as malware, tampering, and compliance violations.
SAAI is a scalable, cloud-native platform that integrates seamlessly into enterprise workflows, delivering real-time threat detection, compliance reporting, and adversarial resilience for Large Language Models (LLMs).
Pre-Scan Validation
SAAI verifies the basic integrity of the model file by comparing it against a trusted baseline. Corrupted or tampered files are rejected early, preventing wasted time on deeper analysis of compromised data.
Malware Detection
SAAI scans the model files for embedded malicious code, such as backdoors hidden in weights or scripts. Using YARA rules tailored to known AI threats, it identifies dangerous patterns like pickle exploits, which have been found in many open-source models, protecting users from security risks before deployment.
Integrity Check
SAAI analyses the internal structure of the model, including layer weights and statistics, to detect anomalies like unexpected sparsity or zeroed-out weights. Using frameworks like PyTorch and numpy, SAAI flags unusual patterns that may indicate tampering or subtle performance degradation.
Compliance Scan
To prevent privacy violations, SAAI inspects metadata and fine-tuning data for personally identifiable information (PII) such as emails or social security numbers. By extracting metadata and applying regex or NLP techniques, it ensures models meet data protection regulations like GDPR and CCPA, avoiding costly penalties.
Adversarial Risk
SAAI evaluates the model’s robustness by feeding adversarial inputs designed to bypass safeguards, such as prompt injections. SAAI scores responses against a rubric to identify vulnerabilities, preventing exploitation scenarios like jailbreak in conversational AI systems
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