About this CFP
At Amazon, we aim to advance innovations that solve some of the most pressing challenges in security. We are seeking to fund research on the following topics:
- Vulnerability detection and remediation using agentic AI
- AI for binary firmware analysis, with a focus on platform and embedded devices firmware
- AI-assisted secure code generation and security enhancement of existing codebases
- Open-Source security. Verifying software supply chain trust; improving memory safety in legacy codebases (e.g., C/C++ to Rust migration); advancing package management and dependency security.
- Authentication and authorization frameworks for AI agents
- Hardware and firmware security (x86 and ARM architectures); hyperscale platform security (interconnect, ASICs, GPUs, NPUs); microarchitecture security; fault injection; virtualization security (KVM, Nitro, Firecracker).
- Trustworthy and reliable agentic AI for hardware security analysis operations, including methodologies for evaluating AI agents in hardware security use cases
- Improving the completeness, consistency, and robustness of agentic AI security analysis across repositories, dependencies, and services, e.g., through hybrid approaches with classic code analysis.
- Technologies to formally verify the absence of security issues or that security properties hold across all executions of the system.
- Measuring the effectiveness and coverage of security tools in the face of evolving threat actor techniques and new types of security risk.
- Vulnerability detection systems that automatically improve themselves when they are notified of false positives or false negatives.
- AI agents that reliably identify when a security analysis is beyond the capabilities of the agent and therefore requires human intervention.
- Low-cost computer vision techniques for object interactions for physical security.
- Near-real-time anomaly detection at scale (e.g., streaming petabytes per hour) to identify malicious activity in Linux cloud-based environments.
- Running distributed big data, AI/ML, and/or streaming models with minimal latency and cost using host, network, and audit telemetry sources. Such data engineering can be used for selecting interesting subsets of data including complex, multi-event sequences, improving matching and micro-summarization efficiencies for continuous log processing, and improving event summarization processing efficiency while maintaining accuracy.
- Automating red team vs. blue team using agentic AI systems
Timeline
- Submission period: March 25 - May 6, 2026 (11:59 PM Pacific Time)
- Decision letters will be sent out in August 2026
Award details
Selected Principal Investigators (PIs) may receive the following:
- Unrestricted funds, no more than $80,000 USD on average
- AWS Promotional Credits, no more than $50,000 USD on average
- Training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers
Awards are structured as one-time unrestricted gifts. The budget should include a list of expected costs specified in USD, and should not include administrative overhead costs. The final award amount will be determined by the awards panel.
Eligibility requirements
Please refer to the ARA Program rules on the Rules and Eligibility page.
Proposal requirements
Proposals should be prepared according to the proposal template and are encouraged to be a maximum of 3 pages, not including Appendices.
Selection criteria
Amazon Security will make the funding decisions based on the potential impact to the research community and quality of the scientific content.
Expectations from recipients
To the extent deemed reasonable, Award recipients should acknowledge the support from ARA. Award recipients will inform ARA of publications, presentations, code and data releases, blogs/social media posts, and other speaking engagements referencing the results of the supported research or the Award. Award recipients are expected to provide updates and feedback to ARA via surveys or reports on the status of their research. Award recipients will have an opportunity to work with ARA on an informational statement about the awarded project that may be used to generate visibility for their institutions and ARA.