AWS Security Blog
Tag: artificial intelligence
Securing the RAG ingestion pipeline: Filtering mechanisms
Retrieval-Augmented Generative (RAG) applications enhance the responses retrieved from large language models (LLMs) by integrating external data such as downloaded files, web scrapings, and user-contributed data pools. This integration improves the models’ performance by adding relevant context to the prompt. While RAG applications are a powerful way to dynamically add additional context to an LLM’s prompt […]
Hardening the RAG chatbot architecture powered by Amazon Bedrock: Blueprint for secure design and anti-pattern mitigation
Mitigate risks like data exposure, model exploits, and ethical lapses when deploying Amazon Bedrock chatbots. Implement guardrails, encryption, access controls, and governance frameworks.
The art of possible: Three themes from RSA Conference 2024
RSA Conference 2024 drew 650 speakers, 600 exhibitors, and thousands of security practitioners from across the globe to the Moscone Center in San Francisco, California from May 6 through 9. The keynote lineup was diverse, with 33 presentations featuring speakers ranging from WarGames actor Matthew Broderick, to public and private-sector luminaries such as Cybersecurity and Infrastructure Security […]
Securing generative AI: data, compliance, and privacy considerations
Generative artificial intelligence (AI) has captured the imagination of organizations and individuals around the world, and many have already adopted it to help improve workforce productivity, transform customer experiences, and more. When you use a generative AI-based service, you should understand how the information that you enter into the application is stored, processed, shared, and […]
Securing generative AI: Applying relevant security controls
This is part 3 of a series of posts on securing generative AI. We recommend starting with the overview post Securing generative AI: An introduction to the Generative AI Security Scoping Matrix, which introduces the scoping matrix detailed in this post. This post discusses the considerations when implementing security controls to protect a generative AI […]
Generate AI powered insights for Amazon Security Lake using Amazon SageMaker Studio and Amazon Bedrock
In part 1, we discussed how to use Amazon SageMaker Studio to analyze time-series data in Amazon Security Lake to identify critical areas and prioritize efforts to help increase your security posture. Security Lake provides additional visibility into your environment by consolidating and normalizing security data from both AWS and non-AWS sources. Security teams can […]
Securing generative AI: An introduction to the Generative AI Security Scoping Matrix
Generative artificial intelligence (generative AI) has captured the imagination of organizations and is transforming the customer experience in industries of every size across the globe. This leap in AI capability, fueled by multi-billion-parameter large language models (LLMs) and transformer neural networks, has opened the door to new productivity improvements, creative capabilities, and more. As organizations […]
Stronger together: Highlights from RSA Conference 2023
RSA Conference 2023 brought thousands of cybersecurity professionals to the Moscone Center in San Francisco, California from April 24 through 27. The keynote lineup was eclectic, with more than 30 presentations across two stages featuring speakers ranging from renowned theoretical physicist and futurist Dr. Michio Kaku to Grammy-winning musician Chris Stapleton. Topics aligned with this […]
How AWS SideTrail verifies key AWS cryptography code
We know you want to spend your time learning valuable new skills, building innovative software, and scaling up applications — not worrying about managing infrastructure. That’s why we’re always looking for ways to help you automate the management of AWS services, particularly when it comes to cloud security. With that in mind, we recently developed […]