We applied AWS Security Agent (now part of AWS Continuum), our autonomous penetration-testing agent, to 37 real, recently disclosed Common Vulnerabilities and Exposures (CVEs), each packaged as a live, containerized target with a flag hidden at the vulnerability’s intended sink. Starting from an unauthenticated or low-privilege position (an …
Most security tooling that fits into a CI/CD pipeline—static analysis (SAST), software composition analysis (SCA), and dynamic scanners (DAST)—flags potential issues from patterns and signatures. A flagged pattern shows you where to look; penetration testing is what confirms whether something is actually exploitable. That confirmation has …
This post shows you how to configure an AI model to perform structured, evidence-based vulnerability triage with the consistency of a seasoned security analyst. You’ll learn the design decisions behind five configuration sections that enforce structural verification, evidence-based scoring, and infrastructure-aware prioritization across every analysis session. Our companion …
Vulnerability scanners produce findings faster than manual triage can process them. Your developers ship more code with more dependencies, and the volume of candidate findings grows with it. Many findings a scanner produces are unlikely to be exploited. The ones that matter need to reach an engineer fast, with …
European organizations can run AI workloads on Amazon Web Services (AWS) while keeping data within the European Union (EU) and meeting regulatory requirements. You can now run generative AI workloads on open weight models on Amazon Bedrock in the AWS European Sovereign Cloud. We’re excited to announce the …
Security teams are starting to actively use AI for security work, including vulnerability triage, penetration testing, threat modeling, incident response, and code review. The promise is speed, but a security tool that moves fast and raises too many false alarms doesn’t save time. Engineers spend time on false …
If you’re running AI agents in production, Amazon Bedrock Guardrails protects the model boundary. But your agents also invoke tools, fetch external data, and communicate with other systems. That data flows outside the model boundary, where model-level guardrails can’t reach. You can extend guardrail coverage to those …
Customers have access to models that are continuously getting better with each new generation bringing larger context windows, stronger reasoning, and lower token costs. Getting the strongest AI-powered security will come from tools that combine the most relevant models with deep knowledge of a customer’s specific environment. AWS …
AI coding agents are part of the developer toolchain. Tools like Kiro and Claude Code generate features, tests, and code refactors from natural-language prompts. A single agent can open dozens of pull requests (PRs) across your repositories in an afternoon. That productivity comes with a trade-off: agents optimize for …
Amazon is sharing new findings about how a threat actor linked to the Democratic People’s Republic of Korea (DPRK) is targeting open source software libraries, the shared building blocks that companies around the world use to develop applications. Amazon Threat Intelligence has linked several recent compromises of popular …
System prompts form the foundation of generative AI applications. A system prompt is a collection of instructions and operational context provided to a large language model (LLM) that shapes how the model behaves and interacts with users and tools. System prompts often contain proprietary information, including role definitions, behavioral …
Agents have agency: they adapt and find multiple ways to solve problems. This autonomy creates a fundamental security challenge: the large language model (LLM) at the heart of the agent is non-deterministic, and its decisions can’t be predicted or guaranteed in advance. It can hallucinate harmful actions with …
The financial services industry (FSI) is using AI to transform how financial institutions serve their customers. AI solutions can help proactively manage portfolios, automatically refinance mortgages when rates decrease, and negotiate insurance premiums for customers. However, this adoption brings new governance, risk, and compliance (GRC) considerations that organizations need …
We have released our latest compliance guide, ISO/IEC 42001:2023 on AWS, which provides practical guidance for organizations designing and operating an Artificial Intelligence Management System (AIMS) using AWS services. As organizations deploy AI and generative AI workloads in the cloud, aligning with globally recognized standards such as …
A Monday morning security alert flags unauthorized access attempts, security group misconfigurations, and AWS Identity and Access Management (IAM) policy violations. Your team needs answers fast. Security teams are using Kiro and Amazon Q Developer to handle repetitive tasks—scanning resources, drafting policies, and researching Common Vulnerabilities and Exposures …
It’s only been a few weeks since Anthropic announced the Claude Mythos Preview model and launched Project Glasswing with AWS and other leading organizations. This has generated a lot of discussion about the future of cybersecurity and what the ever-increasing capabilities of foundation models mean to organizations. As …
At AWS, we’ve spent decades developing processes and tools that enable us to defend millions of customers simultaneously, wherever they operate around the world. Every day, our security and threat intelligence teams are doing work with AI and automation that most people never see. Our AI-powered log analysis …
As generative AI became mainstream, Amazon Web Services (AWS) launched the Generative AI Security Scoping Matrix to help organizations understand and address the unique security challenges of foundation model (FM)-based applications. This framework has been adopted not only by AWS customers across the globe, but also widely referenced …
Google on Wednesday revealed five recent malware samples that were built using generative AI. The end results of each one were far below par with professional malware development, a finding that shows that vibe coding of malicious wares lags behind more traditional forms of development, which means it still …
Recently, AWS released Amazon Bedrock API keys to make calls to the Amazon Bedrock API. In this post, we provide practical security guidance on effectively implementing, monitoring, and managing this new option for accessing Amazon Bedrock to help you build a comprehensive strategy for securing these keys. We also …
Amazon Bedrock Guardrails provides configurable safeguards to help you safely build generative AI applications at scale. It offers integrated safety and privacy protections that work across multiple foundation models (FMs), including models available in Amazon Bedrock and models hosted outside Amazon Bedrock from other providers. Bedrock Guardrails currently offers …
When interacting with AI applications, even seemingly innocent elements—such as Unicode characters—can have significant implications for security and data integrity. At Amazon Web Services (AWS), we continuously evaluate and address emerging threats across aspects of AI systems. In this blog post, we explore Unicode tag blocks, a …
As generative AI becomes foundational across industries—powering everything from conversational agents to real-time media synthesis—it simultaneously creates new opportunities for bad actors to exploit. The complex architectures behind generative AI applications expose a large surface area including public-facing APIs, inference services, custom web applications, and integrations with …
In Part 1 of this series, we explored the fundamental risks and governance considerations. In this part, we examine practical strategies for adapting your enterprise risk management framework (ERMF) to harness generative AI’s power while maintaining robust controls. This part covers: Adapting your ERMF for the cloud Adapting …
According to BCG research, 84% of executives view responsible AI as a top management responsibility, yet only 25% of them have programs that fully address it. Responsible AI can be achieved through effective governance, and with the rapid adoption of generative AI, this governance has become a business imperative …