AI Market Logo
BTC $43,552.88 -0.46%
ETH $2,637.32 +1.23%
BNB $312.45 +0.87%
SOL $92.40 +1.16%
XRP $0.5234 -0.32%
ADA $0.8004 +3.54%
AVAX $32.11 +1.93%
DOT $19.37 -1.45%
MATIC $0.8923 +2.67%
LINK $14.56 +0.94%
HAIA $0.1250 +2.15%
BTC $43,552.88 -0.46%
ETH $2,637.32 +1.23%
BNB $312.45 +0.87%
SOL $92.40 +1.16%
XRP $0.5234 -0.32%
ADA $0.8004 +3.54%
AVAX $32.11 +1.93%
DOT $19.37 -1.45%
MATIC $0.8923 +2.67%
LINK $14.56 +0.94%
HAIA $0.1250 +2.15%
Project Ire: Microsoft's autonomous malware detection AI agent
malware-detection

Project Ire: Microsoft's autonomous malware detection AI agent

Microsoft’s Project Ire prototype autonomously detects malware with high accuracy, promising advances in AI-driven cybersecurity.

August 6, 2025
5 min read
Zeljka Zorz

Microsoft’s Project Ire prototype autonomously detects malware with high accuracy, promising advances in AI-driven cybersecurity.

Project Ire: Microsoft’s AI-Powered Autonomous Malware Detection Agent

Microsoft is developing an AI agent focused on autonomous malware detection. The prototype, called Project Ire, is showing promising results, according to a company announcement on August 5, 2025. Tested on a dataset of known malicious and benign Windows drivers, Project Ire correctly identified 90% of all files and flagged only 2% of benign files as threats. In a separate test involving nearly 4,000 files that Microsoft’s automated systems could not classify and that had not been manually reviewed by expert reverse engineers, the prototype correctly flagged nearly 90% of malicious files. It maintained a low false positive rate of 4% but detected about a quarter of all actual malware.
“While overall performance was moderate, this combination of accuracy and a low error rate suggests real potential for future deployment,” the research team noted.

About Project Ire

Currently in the prototype phase, Project Ire leverages advanced language models available through Azure AI Foundry alongside various reverse engineering and binary analysis tools. The evaluation process begins with automated reverse engineering to determine the file type, structure, and highlight areas requiring closer inspection. After triage, the system reconstructs the software’s control flow graph using frameworks such as angr and Ghidra. This graph maps program execution, enabling an iterative analysis of each function with the help of language models and specialized tools. Summaries of these analyses are compiled into a “chain of evidence” record, providing transparency into the system’s reasoning. This record allows security teams to review results and helps developers refine the system when misclassifications occur. Project Ire applies Microsoft’s public criteria to classify samples as malware, potentially unwanted applications, tampering software, or benign files. To verify findings, Project Ire can invoke a validator tool that cross-checks claims against the chain of evidence. This tool incorporates expert statements from malware reverse engineers on the Project Ire team. Using this evidence and its internal model, the system generates a final report classifying the sample as malicious or benign. Project Ire’s report on a kernel-level rootkit (Source: Microsoft) There have been instances where the AI agent’s reasoning contradicted human experts but was later proven correct. Mike Walker, Research Manager at Microsoft, told Help Net Security that these cases demonstrate the complementary strengths of humans and AI in protection.
“Our system is designed to capture risk reasoning at each step, and it’s critical to have a detailed audit trail of line-of-reasoning to allow for deeper investigation of the system.”
Project Ire will be integrated into Microsoft Defender as a binary analyzer tool for threat detection and software classification. Ultimately, researchers hope Project Ire will autonomously detect novel malware directly in memory at scale.
Source: Originally published at Help Net Security on August 5, 2025.

Frequently Asked Questions (FAQ)

Project Ire's Capabilities and Development

Q: What is Project Ire? A: Project Ire is a prototype AI agent developed by Microsoft for autonomous malware detection. Q: What kind of results has Project Ire shown in its tests? A: In tests on known malicious and benign Windows drivers, Project Ire achieved 90% accuracy in identifying all files and flagged only 2% of benign files as threats. It also correctly flagged nearly 90% of malicious files in a dataset that automated systems could not classify, with a 4% false positive rate. Q: What technologies does Project Ire utilize? A: Project Ire uses advanced language models from Azure AI Foundry and integrates various reverse engineering and binary analysis tools. Q: How does Project Ire analyze files? A: It begins with automated reverse engineering, followed by control flow graph reconstruction using frameworks like angr and Ghidra. This allows for iterative analysis with language models and specialized tools. Q: What is the "chain of evidence" in Project Ire's process? A: The "chain of evidence" is a record of the system's analysis summaries, providing transparency into its reasoning. This helps security teams review results and developers refine the system. Q: How does Project Ire classify samples? A: It applies Microsoft's public criteria to classify files as malware, potentially unwanted applications, tampering software, or benign files. Q: Can Project Ire's findings be independently verified? A: Yes, Project Ire can invoke a validator tool that cross-checks its claims against the chain of evidence, incorporating expert statements from the development team. Q: Have there been instances where Project Ire's reasoning differed from human experts? A: Yes, there have been cases where Project Ire's reasoning contradicted human experts but was later proven correct, highlighting the complementary strengths of AI and human analysis. Q: What is the future deployment plan for Project Ire? A: Project Ire is planned for integration into Microsoft Defender as a binary analyzer tool for threat detection and software classification, with the ultimate goal of autonomously detecting novel malware in memory at scale.

Crypto Market AI's Take

Microsoft's development of Project Ire signifies a significant advancement in AI-driven cybersecurity. The increasing sophistication of malware necessitates equally advanced detection methods, and autonomous AI agents like Project Ire are at the forefront of this evolution. This technology has broader implications, as AI is rapidly transforming various sectors, including the financial markets. Our platform, Crypto Market AI, leverages AI for market analysis and trading, demonstrating how AI can enhance efficiency and provide valuable insights across different industries. The advancements in AI for cybersecurity, as seen with Project Ire, also parallel the need for robust security in the cryptocurrency space, where sophisticated threats require constant vigilance and innovative solutions.

More to Read: