-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
Hey HN,
We're building Aegis, a firewall for LLMs: a guard against adversarial attacks, prompt injections, toxic language, PII leakage, etc.
One of the primary concerns entwined with building LLM applications is the chance of attackers subverting the model’s original instructions via untrusted user input, which unlike in SQL injection attacks, can’t be easily sanitized. (See https://greshake.github.io/ for the mildest such instance.) Because the consequences are dire, we feel it’s better to err on the side of caution, with something mutli-pass like Aegis, which consists of a lexical similarity check, a semantic similarity check, and a final pass through an ML model.
We'd love for you to check it out—see if you can prompt inject it!, and give any suggestions/thoughts on how we could improve it: https://github.com/automorphic-ai/aegis.
If you want to play around with it without creating an account, try the playground: https://automorphic.ai/playground.
If you're interested in or need help using Aegis, have ideas, or want to contribute, join our [Discord](https://discord.com/invite/E8y4NcNeBe), or feel free to reach out at [email protected]. Excited to hear your feedback!
Repository: https://github.com/automorphic-ai/aegis
Related posts
-
We’ve built a free firewall for LLMs (Aegis) — Say goodbye to prompt injections, prompt leakage, and toxic language (100+ stars)
-
Try your best prompts—especially prompt injections—against Aegis, our firewall for LLMs
-
Show HN: Times faster LLM evaluation with Bayesian optimization
-
Validating the RAG Performance of Amazon Titan vs. Cohere Using Amazon Bedrock
-
Tonic.ai and LlamaIndex join forces to help developers build RAG systems