fuzzing-dictionary

Fuzzing Dictionary

A fuzzing dictionary provides domain-specific tokens to guide the fuzzer toward interesting inputs. Instead of purely random mutations, the fuzzer incorporates known keywords, magic numbers, protocol commands, and format-specific strings that are more likely to reach deeper code paths in parsers, protocol handlers, and file format processors.

Overview

Dictionaries are text files containing quoted strings that represent meaningful tokens for your target. They help fuzzers bypass early validation checks and explore code paths that would be difficult to reach through blind mutation alone.

Key Concepts

When to Apply

Apply this technique when:

• Fuzzing parsers (JSON, XML, config files)
• Fuzzing protocol implementations (HTTP, DNS, custom protocols)
• Fuzzing file format handlers (PNG, PDF, media codecs)
• Coverage plateaus early without reaching deeper logic
• Target code checks for specific keywords or magic values

Skip this technique when:

• Fuzzing pure algorithms without format expectations
• Target has no keyword-based parsing
• Corpus already achieves high coverage

Quick Reference

Step-by-Step

Step 1: Create Dictionary File

Create a text file with quoted strings on each line. Use comments (#) for documentation.

Example dictionary format:

# Lines starting with '#' and empty lines are ignored.
 
# Adds "blah" (w/o quotes) to the dictionary.
kw1="blah"
# Use \\ for backslash and \

Step 2: Generate Dictionary Content

Choose a generation method based on what's available:

From LLM: Prompt ChatGPT or Claude with:

From header files:

From man pages (for CLI tools):

From binary strings:

Step 3: Pass Dictionary to Fuzzer

Use the appropriate flag for your fuzzer (see Quick Reference above).

Common Patterns

Pattern: Protocol Keywords

Use Case: Fuzzing HTTP or custom protocol handlers

Dictionary content:

Pattern: Magic Bytes and File Format Headers

Use Case: Fuzzing image parsers, media decoders, archive handlers

Dictionary content:

Pattern: Configuration File Keywords

Use Case: Fuzzing config file parsers (YAML, TOML, INI)

Dictionary content:

Advanced Usage

Tips and Tricks

Auto-Generated Dictionaries (AFL++)

When using afl-clang-lto compiler, AFL++ automatically extracts dictionary entries from string comparisons in the binary. This happens at compile time via the AUTODICTIONARY feature.

Enable auto-dictionary:

Combining Multiple Dictionaries

Some fuzzers support multiple dictionary files:

Anti-Patterns

Tool-Specific Guidance

libFuzzer

Integration tips:

• Dictionary tokens are inserted/replaced during mutations
• Combine with -max_len to control input size
• Use -print_final_stats=1 to see dictionary effectiveness metrics
• Dictionary entries longer than -max_len are ignored

AFL++

Integration tips:

• AFL++ supports multiple -x flags for multiple dictionaries
• Use AFL_LLVM_DICT2FILE with afl-clang-lto for auto-generated dictionaries
• Dictionary effectiveness shown in fuzzer stats UI
• Tokens are used during deterministic and havoc stages

cargo-fuzz (Rust)

Integration tips:

• cargo-fuzz uses libFuzzer backend, so all libFuzzer dict flags work
• Place dictionary file in fuzz/ directory alongside harness
• Reference from harness directory: cargo fuzz run target -- -dict=../dictionary.dict

go-fuzz (Go)

go-fuzz does not have built-in dictionary support, but you can manually seed the corpus with dictionary entries:

Troubleshooting

Related Skills

Tools That Use This Technique

Related Techniques

Resources

Key External Resources

AFL++ Dictionaries Pre-built dictionaries for common formats (HTML, XML, JSON, SQL, etc.). Good starting point for format-specific fuzzing.

libFuzzer Dictionary Documentation Official libFuzzer documentation on dictionary format and usage. Explains token insertion strategy and performance implications.

Additional Examples

OSS-Fuzz Dictionaries Real-world dictionaries from Google's continuous fuzzing service. Search project directories for *.dict files to see production examples.`