Intelligence Pipeline

12 Phases. 228 Engines. Zero Guesswork.

Most binary analysis tools give you a confidence score and ask you to trust it. We don't. Instead, we show you exactly how every conclusion was reached — step by step, byte by byte.

01

Binary Ingest

Gate
Engines 1–20·Gate: Format Verified

The system opens your file and answers the most basic question: what is this thing? It reads the first few bytes to identify the format. ELF files start with 7F 45 4C 46. PE files start with MZ. Once identified, the engines extract the internal structure: executable code, data, strings, and compiler metadata.

Why it matters

90% of analysts waste their first hour just figuring out what a binary is. B2E does it in 1.2 seconds.

02

Instruction Decode

Gate
Engines 21–40·Gate: Architecture Confirmed

Machine code is just numbers. The number 0x55 on an x86 processor means "push the base pointer." This phase figures out the processor architecture and translates every machine instruction into human-readable assembly language.

x86x86-64ARMMIPSPowerPCRISC-V

Why it matters

Without accurate instruction decoding, every subsequent analysis phase would be working with garbage data.

03

Control Flow Analysis

Gate
Engines 41–60·Gate: Graph Complete

Maps every decision point — every if/else, every switch statement, every loop. The result is a control flow graph showing every possible path through the code. Hidden behavior starts to surface here: functions that only execute on specific dates, code paths that activate on network failures.

Why it matters

Malware authors hide their most dangerous code behind obscure conditions. The control flow graph reveals every possible execution path.

04

Memory Analysis

Engines 61–80

Tracks heap allocations, stack usage, pointer relationships, and buffer boundaries. Finds buffer overflows and use-after-free errors automatically — the most common and most dangerous class of software vulnerabilities.

Why it matters

Memory corruption vulnerabilities are the most common and most dangerous class of software bugs.

05

Dataflow Analysis

Engines 81–90

Traces every piece of data from entry to sensitive operation. Taint analysis marks untrusted data and follows it through every transformation. If user input reaches a format string function without sanitization, this phase flags it.

Why it matters

Most vulnerabilities aren't individual bugs — they're data paths. Unsafe data flowing through functions that never validate it.

06

Semantic Analysis

Gate
Engines 91–100·Gate: Behavioral Profile Complete

Classifies every function by purpose: cryptographic operations, networking, file manipulation, process injection, privilege escalation, anti-analysis techniques, and persistence mechanisms. Determines whether a connect() call is a legitimate HTTPS request or a covert command-and-control channel.

Why it matters

Understanding individual instructions is necessary but not sufficient. You need to understand intent.

07

Decompilation

Engines 101–120

Translates assembly back into C-like pseudocode with inferred types and meaningful variable names. Replaces var_28h with encryption_key based on usage context. The result is code readable by anyone with basic programming knowledge.

Why it matters

When the report says "this function encrypts a buffer using AES-256," the decompiled pseudocode lets you verify that claim.

08

Knowledge Base Matching

Gate
Engines 121–140·Gate: Enrichment Verified

Compares against 8.7 million malware signatures, known CVEs, compiler fingerprints, and API behavior databases. If the binary uses broken cryptography like DES-ECB, this phase flags it. If it matches a known malware family, this phase identifies the variant.

Why it matters

Your binary doesn't exist in isolation. It exists in the context of every vulnerability ever cataloged.

09

Natural Language Generation

Engines 141–160

All technical analysis is translated into professional, structured English. The NLG engines produce fluid, contextual narratives tailored to 10 distinct analysis profiles. A Malware Analyst report emphasizes kill chains. A Compliance Auditor report emphasizes regulatory controls.

Why it matters

Raw technical data is useless if the person reading it can't act on it.

10

Machine Learning Calibration

Engines 161–180

Cross-references findings against patterns from thousands of binaries to calibrate confidence scores. A finding confirmed by multiple independent techniques gets higher confidence. A finding relying on a single heuristic gets a lower score with an explicit caveat.

Why it matters

Overconfident tools waste time with false positives. Underconfident tools miss real threats.

11

Validation & Output

Gate
Engines 181–200·Gate: 240 QA Checks Passed

240 automated QA checks verify: evidence references point to real bytes, claims are supported by analysis techniques, confidence scores are consistent, narrative matches underlying data, internal terms are removed. Nothing reaches you without passing all 240 checks.

Why it matters

This is the difference between a tool you use and a tool you trust.

12

Dynamic Analysis

Optional
Engines 201–220

Binary executed in a sealed QEMU sandbox with no network access. Watches runtime behavior: file creation, network attempts, system calls, and memory mutations. Runtime data is correlated with static analysis from all previous phases.

Why it matters

Some behaviors are invisible in static analysis. A binary that unpacks at runtime can only be fully understood by watching it execute.

Quality Assurance

The Verification Matrix

Every finding is tracked across four measurement dimensions. These four values always sum to 1.0, ensuring no single aspect can inflate the overall confidence.

01

Technical Precision

How much raw technical detail supports this finding? Every claim is backed by hex offsets and instruction addresses.

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02

Structural Depth

How deeply nested in the program's architecture is this behavior? Measures coverage of functions, branches, and data structures.

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03

Confidence Level

How many independent analysis techniques confirm this finding? Cross-validated across multiple engines.

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04

Temporal Context

When in the program's execution lifecycle does this behavior occur? Maps findings to time-dependent activation.

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No other binary analysis tool on the market gives you this level of mathematical transparency about its own certainty.

What's Hiding in Your Binary?

Right now, compiled software is running on your servers, embedded in your devices, and processing your customers' data. You didn't write it. You can't read the source code. You're trusting it because someone told you to.

228 engines12 phasesFull report in minutes