Benchmarking DeepDiff Against BinDiff on Stripped and Cross-Compiler Binaries
Sheng Yu, Research Scientist @Deepbits
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All posts →Lessons from Building Agentic Binary Analysis, Part 1: LLMs Skim, They Don't Explore.
The most fundamental failure mode of LLM-powered binary analysis: models evaluate binaries by their most obvious features and stop there. This post walks through how Dr. Binary addresses it with an exhaustive analysis tool that processes every function before the LLM draws any conclusions.
Agentic Binary Analysis: When AI Becomes the Analyst
Exploring how autonomous AI agents are revolutionizing binary code analysis through self-directed reasoning, collaborative multi-agent systems, and adaptive threat detection strategies that operate without human intervention.
DeepDiff: Next-Generation Binary Diffing for Precise Vulnerability and Patch Detection
We're excited to announce the launch of DeepDiff, Deepbits' groundbreaking solution for vulnerability detection and binary diffing. DeepDiff represents a major leap forward in security analysis. It helps security researchers, reverse engineers, and development teams to pinpoint vulnerable functions and generate precise diffing views across binary files with unmatched accuracy.